# HG changeset patch
# User computational-metabolomics
# Date 1586638099 14400
# Node ID 62c4813fbe7a6d8112157fa11de71628f8056ad1
"planemo upload for repository https://github.com/computational-metabolomics/dimspy-galaxy commit 6321871098b2c4bc9e321d20b7e66fff3d641839"
diff -r 000000000000 -r 62c4813fbe7a README.rst
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/README.rst Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,66 @@
+Galaxy tool wrappers for DIMSpy
+========================
+|Build Status (Travis)| |Git| |Bioconda| |License|
+
+Galaxy tool wrappers for Python package DIMSpy: data processing of direct-infusion mass spectrometry (DIMS)-based metabolomics and lipidomics data
+
+Source code: https://github.com/computational-metabolomics/dimspy
+
+PyPI (The Python Package Index): https://pypi.org/project/dimspy
+
+
+Version
+--------
+v1.4.0+Galaxy0 (`DIMSpy v1.4.0 `_)
+
+
+Galaxy
+-------
+`Galaxy `_ is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.
+
+
+Authors, contributors & Contacts
+----------------------------------
+ - Ralf J. M. Weber (r.j.weber@bham.ac.uk) - `University of Birmingham (UK) `_
+ - Thomas N. Lawson (tnl495@bham.ac.uk) - `University of Birmingham (UK) `_
+ - Martin R. Jones (m.r.jones.1@bham.ac.uk) - `University of Birmingham (UK) `_
+
+
+Bugs
+----
+Please report any bugs that you find `here `_.
+Or fork the repository on `GitHub `_
+and create a pull request (PR). We welcome all contributions, and we
+will help you to make the PR if you are new to `git`.
+
+
+Changes
+-------
+v1.4.0+galaxy0
+ - First stable release
+ - Final release (Python 2-based version `DIMSpy `_)
+
+
+Licenses
+-------
+DIMSpy and Galaxy tools are released under the GNU General Public License v3.0 (see `LICENSE file `_)
+
+**Third-party licenses and copyright**
+
+RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights reserved. See `RawFileReaderLicense `_ for licensing information.
+Using DIMSpy software for processing Thermo Fisher Scientific *.raw files implies the acceptance of the RawFileReader license terms.
+Anyone receiving RawFileReader as part of a larger software distribution (in the current context, as part of DIMSpy) is considered an "end user" under
+section 3.3 of the RawFileReader License, and is not granted rights to redistribute RawFileReader.
+
+
+.. |Build Status (Travis)| image:: https://img.shields.io/travis/computational-metabolomics/dimspy-galaxy.svg?style=flat&maxAge=3600&label=Travis-CI
+ :target: https://travis-ci.com/computational-metabolomics/dimspy-galaxy
+
+.. |Git| image:: https://img.shields.io/badge/repository-GitHub-blue.svg?style=flat&maxAge=3600
+ :target: https://github.com/computational-metabolomics/dimspy
+
+.. |Bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat&maxAge=3600
+ :target: http://bioconda.github.io/recipes/dimspy/README.html
+
+.. |License| image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg
+ :target: https://www.gnu.org/licenses/gpl-3.0.html
diff -r 000000000000 -r 62c4813fbe7a RawFileReaderLicense.md
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/RawFileReaderLicense.md Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,51 @@
+**SOFTWARE LICENSE AGREEMENT ("License") FOR RawFileReader**
+
+These License terms are an agreement between you and Thermo Finnigan LLC ("Licensor"). They apply to Licensor's MSFileReader software program ("Software"), which includes documentation and any media on which you received it. These terms also apply to any updates or supplements for this Software, unless other terms accompany those items, in which case those terms apply. **If you use this Software, you accept this License. If you do not accept this License, you are prohibited from using this software. If you comply with these License terms, you have the rights set forth below.**
+
+1. Rights Granted:
+
+1.1. You may install and use this Software on any of your computing devices.
+
+1.2. You may distribute this Software to others, but only in combination with other software components and/or programs that you provide and subject to the distribution requirements and restrictions below.
+
+2. Use Restrictions:
+
+2.1. You may not decompile, disassemble, reverse engineer, use reflection or modify this Software.
+
+3. Distribution Requirements:
+
+If you distribute this Software to others, you agree to:
+
+3.1. Indemnify, defend and hold harmless the Licensor from any claims, including attorneys' fees, related to the distribution or use of this Software;
+
+3.2. Display the following text in your software's "About" box: " **RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights reserved**.";
+
+3.3. Require your end users to agree to a license agreement that prohibits them from redistributing this Software to others.
+
+4. Distribution Restrictions:
+
+4.1. You may not use the Licensor's trademarks in a way that suggests your software components and/or programs are provided by or are endorsed by the Licensor; and
+
+4.2. You may not commercially exploit this Software or products that incorporate this Software without the prior written consent of Licensor. Commercial exploitation includes, but is not limited to, charging a purchase price, license fee, maintenance fee, or subscription fee; or licensing, transferring or redistributing the Software in exchange for consideration of any kind.
+
+4.3. Your rights to this Software do not include any license, right, power or authority to subject this Software in whole or in part to any of the terms of an Excluded License. "Excluded License" means any license that requires as a condition of use, modification and/or distribution of software subject to the Excluded License, that such software or other software combined and/or distributed with such software be (a) disclosed or distributed in source code form; or (b) licensed for the purpose of making derivative works. Without limiting the foregoing obligation, you are specifically prohibited from distributing this Software with any software that is subject to the General Public License (GPL) or similar license in a manner that would create a combined work.
+
+5. Additional Terms Applicable to Software:
+
+5.1. This Software is licensed, not sold. This License only gives you some rights to use this Software; the Licensor reserves all other rights. Unless applicable law gives you more rights despite this limitation, you may use this Software only as expressly permitted in this License.
+
+5.2. Licensor has no obligation to fix, update, supplement or support this Software.
+
+5.3. This Software is not designed, manufactured or intended for any use requiring fail-safe performance in which the failure of this Software could lead to death, serious personal injury or severe physical and environmental damage ("High Risk Activities"), such as the operation of aircraft, medical or nuclear facilities. You agree not to use, or license the use of, this Software in connection with any High Risk Activities.
+
+5.4. Your rights under this License terminate automatically if you breach this License in any way. Termination of this License will not affect any of your obligations or liabilities arising prior to termination. The following sections of this License shall survive termination: 2.1, 3.1, 3.2, 3.3, 4.1, 4.2, 4.3, 5.1, 5.2, 5.3, 5.5, 5.6, 5.7, 5.8, and 5.9.
+
+5.5. This Software is subject to United States export laws and regulations. You agree to comply with all domestic and international export laws and regulations that apply to this Software. These laws include restrictions on destinations, end users and end use.
+
+5.6. This License shall be construed and controlled by the laws of the State of California, U.S.A., without regard to conflicts of law. You consent to the jurisdiction of the state and federal courts situated in the State of California in any action arising under this License. The application of the U.N. Convention on Contracts for the International Sale of Goods to this License is hereby expressly excluded. If any provision of this License shall be deemed unenforceable or contrary to law, the rest of this License shall remain in full effect and interpreted in an enforceable manner that most nearly captures the intent of the original language.
+
+5.7. THIS SOFTWARE IS LICENSED "AS IS". YOU BEAR ALL RISKS OF USING IT. LICENSOR GIVES NO AND DISCLAIMS ALL EXPRESS AND IMPLIED WARRANTIES, REPRESENTATIONS OR GUARANTEES. YOU MAY HAVE ADDITIONAL CONSUMER RIGHTS UNDER YOUR LOCAL LAWS WHICH THIS LICENSE CANNOT CHANGE. TO THE EXTENT PERMITTED UNDER YOUR LOCAL LAWS, LICENSOR EXCLUDES THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT.
+
+5.8. LICENSOR'S TOTAL LIABILITY TO YOU FOR DIRECT DAMAGES ARISING UNDER THIS LICENSE IS LIMITED TO U.S. $1.00. YOU CANNOT RECOVER ANY OTHER DAMAGES, INCLUDING CONSEQUENTIAL, LOST PROFITS, SPECIAL, INDIRECT OR INCIDENTAL DAMAGES, EVEN IF LICENSOR IS EXPRESSLY MADE AWARE OF THE POSSIBILITY THEREOF OR IS NEGLIGENT. THIS LIMITATION APPLIES TO ANYTHING RELATED TO THIS SOFTWARE, SERVICES, CONTENT (INCLUDING CODE) ON THIRD PARTY INTERNET SITES, OR THIRD PARTY PROGRAMS, AND CLAIMS FOR BREACH OF CONTRACT, BREACH OF WARRANTY, GUARANTEE OR CONDITION, STRICT LIABILITY, NEGLIGENCE, OR OTHER TORT TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+
+5.9. Use, duplication or disclosure of this Software by the U.S. Government is subject to the restricted rights applicable to commercial computer software (under FAR 52.227019 and DFARS 252.227-7013 or parallel regulations). The manufacturer for this purpose is Thermo Finnigan LLC, 355 River Oaks Parkway, San Jose, California 95134, U.S.A.
diff -r 000000000000 -r 62c4813fbe7a macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,310 @@
+
+ 1.4.0
+ 0
+
+
+
+ dimspy
+
+
+
+
+ dimspy hdf5-pm-to-txt
+ --input '$hdf5_file_out'
+ --output '$matrix_file_out'
+ --delimiter $delimiter
+ --attribute_name $hdf5_to_txt.matrix_attr
+ --representation-samples $hdf5_to_txt.representation_samples
+
+
+
+ dimspy hdf5-pm-to-txt
+ --input '$hdf5_file_out'
+ --output '$matrix_comprehensive_file_out'
+ --delimiter $delimiter
+ --comprehensive
+ --attribute_name $hdf5_to_txt.matrix_attr
+ --representation-samples $hdf5_to_txt.representation_samples
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ hdf5_to_txt["standard"] is True
+
+
+ hdf5_to_txt["comprehensive"] is True
+
+
+
+
+
+ 10.1038/nprot.2016.156
+ 10.1038/sdata.2014.12
+ 10.1021/ac062446p
+ 10.1021/ac2001803
+
+
+
+
+
+
+
+
+
+ - **mz** - the mass-to-charge ratio of the extracted mass spectral peak
+
+ - **intensity** - the intensity of the extracted mass spectral peak
+
+ - **snr** - the signal-to-noise ratio of the extracted peak, which is defined as the ratio of the peak’s intensity value to that of the background noise intensity value
+
+ - **present** - a numeric value greater than 0 that indicates the total number of scans at least one peak was detected in a given file
+
+ - **fraction** - a proportion ranging from 0 to 1 that indicates the total number of times a peak was detected in a given scan event type, divided by the total number of occurrences of that scan event type recorded in a given file.
+
+ - **purity** - a numeric value ranging from 0 to 1 that indicates the proportion of scans, for a given scan event type, that contained a single mass spectral peak following hierarchical clustering. A purity score less-than 1 indicates that in some proportion of scans, multiple peaks within a single scan were grouped together during the hierarchical clustering process.
+
+ - **occurrence** - a numeric value greater than 0 that indicates the total number of peaks that were observed across scans within the user-defined ppm error tolerance.
+
+ - **snr_flag** - a boolean value indicating whether to keep (“1”) or discard (“0”) a peak according to its signal-to-noise ratio value.
+
+ - **fraction_flag** - a boolean value indicating whether a peak should be kept or discarded according to the ratio of the number of scans in which it was detected, to the the number of scans in which it was not detected.
+
+ - **flags** - a boolean value indicating whether a peak should be retained or discarded based upon both its ‘snr_flag’ and ‘fraction_flag’ boolean values (if either is set to ‘0’ i.e. discard peak, then the ‘flags’ boolean should also be 0).
+
+
+
+
+
+
+**Example of an processed and filtered peaklist**:
+
+
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| mz | intensity | snr | present | fraction | rsd | occurrence | purity | snr_flag | fraction_flag | flags |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 90.44000 | 4744.0 | 3.06 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 97.07380 | 5423.6 | 3.52 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.04180 | 4105.8 | 3.60 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.49800 | 4775.7 | 3.05 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.95020 | 5657.8 | 3.63 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 100.40660 | 5489.5 | 3.57 | 3 | 0.188 | 14.51 | 3 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 100.8672 | 4841.18 | 3.27 | 7 | 0.4375 | 16.36 | 7 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0027 | 9047.79 | 5.99 | 16 | 1 | 21.53 | 19 | 0.8125 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0033 | 271893.9 | 182 | 16 | 1 | 4.17 | 16 | 1 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0038 | 8738.03 | 5.9 | 14 | 0.875 | 9.71 | 14 | 1 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.004 | 5166.67 | 3.5 | 5 | 0.3125 | 18.02 | 6 | 0.8 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0599 | 5894.69 | 3.88 | 2 | 0.125 | 15.06 | 2 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.2728 | 6846.28 | 4.44 | 1 | 0.0625 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+
+
+
+
+
+**Show options for additional output(s)** (OPTIONAL):
+
+- **Standard output** (default = **No**) - boolean toggle where selection of:
+
+ - **No** - prevent the export of a .txt formatted peak matrix to the active Galaxy history.
+
+ - **Yes** - export a .txt formatted peak matrix to the active Galaxy history that includes only those peaks from the input peak intensity matrix that passed the filtering procedure.
+
+- **Comprehensive output** (default = "No") - boolean toggle where selection of:
+
+ - **No** - prevents export of a .txt formatted comprehensive peak matrix.
+
+ - **Yes** - exports a .txt formatted comprehensive peak matrix to the active Galaxy history that contains the m/z, missing values and other metrics associated with all peaks included in the input peak intensity matrix, including the metric defined by the "The peak matrix should contain intensity | m/z | SNR values" parameter.
+
+- **Should rows or columns represent the samples?** (default = **rows**) - binary toggle where selection of:
+
+ - **rows** - sample information is presented in the rows and m/z values (for aligned mass spectral peaks) in the columns of any output peak matrix.
+
+ - **columns** - sample information is presented in the columns and m/z values (for aligned mass spectral peaks) in the rows of any output peak matrix.
+
+- **The peak matrix should contain intensity | m/z | SNR values** - use this option to define which peak metric is inserted in to the cells of any optionally-output peak matrix:
+
+ - **Intensity** - writes the absolute peak intensity to the cells of the peak matrix
+
+ - **m/z** - writes the mass-to-charge ratio to the cells of the peak matrix
+
+ - **signal-to-noise ratio (SNR)** - writes the signal-to-noise ratio to the cells of the peak matrix
+
+
+
+
+
+**Default output** - a HDF5 file containing the aligned peak intensity matrix.
+
+|
+
+**Optional outputs** - the metric recorded in any optionally output peak matrix/matrices is defined using the parameter "The peak matrix should contain intensity | m/z | SNR values". By default, study samples are listed row-wise, while mass-to-charge ratios of the aligned mass spectral peaks are presented in columns (to adjust, users must adjust the "Should rows or columns represent samples" toggle to “columns”).
+
+
+- **Standard output** - an aligned peak matrix in tab-delimited format (“.” as decimal and NA for missing values).
+
+ **Example of a standard peak intensity matrix**:
+
+ +------------+----------+----------+----------+----------+---------+
+ | mz | 96.04216 | 99.08062 | 100.0759 | 100.8672 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | QC_1 | 0 | 0 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Blank_1 | 3342.626 | 0 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_10 | 0 | 0 | 45432.2 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 0 | 3423.3 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_5 | 0 | 0 | 49759 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_10 | 0 | | 39890.5 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_20 | 0 | 14563.7 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 0 | 34676.4 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_14 | 0 | 13134.9 | 0 | 521.4 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | ... | ... | ... | ... | ... | ... |
+ +------------+----------+----------+----------+----------+---------+
+
+ |
+
+- **Comprehensive output** - an aligned peak matrix, as described for the "standard output" (above), including all metadata from the "Process Scans" Filelist/samplelist and the following additional mass spectral peak metrics:
+
+ - **present** - a positive integer value (0 value total number of study samples in the filelist / samplelist) that indicates the total number of study samples in which a peak was detected with the specified mass-to-charge ratio, plus or minus the user-defined ppm error tolerance.
+
+ - **occurrence** - a positive integer value indicating the number of peaks that were grouped together during the alignment procedure and thus, that were used to calculate the average mass-to-charge ratio indicated for the aligned peak. A value greater than given in the “Present” metric indicates that one or more peaklists contained more-than one mass spectral peak with the specified mass-to-charge, plus or minus the user-defined ppm error tolerance.
+
+ - **purity** - a proportion ranging from 0 to 1 that indicates the number of scans in which only a single peak was detected during the peaklist alignment process. If the value in the “occurrence” metric is greater than the “present” metric, purity will be 1. A purity 1 means that in at least one peaklist there was more-than one mass spectral peak with the specified mass-to-charge, plus or minus the user-defined ppm error tolerance.
+
+ - **rsd_all** - a numeric value indicating the percent relative standard deviation (otherwise termed the percent coefficient of variation) of peak intensities for peaks aligned together using the Align Samples tool. If fewer than 2 peaks were aligned across samples, then the rsd_all column will be filled in with ‘nan’
+
+ - **blank_flag** (may be absent if "Blank filter” tool was not applied) - a boolean value where 0 = reject peak, 1 = accept peak. A peak is accepted during blank filtering if a user-defined minimum proportion of study samples had peak intensity values greater-than the product of the average of “reference” sample peak intensities and the “min_fold_change” parameter.
+
+ - **fraction_flag** (may be absent if "Sample filter” tool was not applied)- a boolean value where 0 = reject peak, 1 = accept peak. If greater-than a user-defined minimum fraction of samples (whether checked across ALL experimental classes, or within ANY of the individual experimental classes) had recorded intensity values for a given peak, then this peak is accepted, i.e. it is considered in downstream processing procedures, while rejected peaks are not.
+
+ - **flags** - a boolean value indicating whether a peak should be included (“1”) or excluded (“0”) from downstream processing procedures. Exclusion of a peak occurs if the thresholds for “relative standard deviation” and/or “minimum number of technical replicates a peak has to be present in” were not met.
+
+ |
+
+ **Example of a comprehensive peak intensity matrix**:
+
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | mz | missing values | tags_batch | tags_replicates | tags_replicate | tags_injectionOrder | tags_classLabel | tags_untyped | 96.04216 | 99.08062 | 100.0759 | 100.8672 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | present* | | | | | | | | 1 | 4 | 3 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | occurrence* | | | | | | | | 1 | 4 | 4 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | purity* | | | | | | | | 1 | 1 | 1 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | rsd_all* | | | | | | | | nan | nan | 10.98 | nan | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | flags* | | | | | | | | 1 | 1 | 1 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | QC_1 | 2901 | 1 | 2_3_4 | 2 | 2 | QC | | 0 | 0 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Blank_1 | 2948 | 1 | 1_2_4 | 1 | 5 | Blank | | 3342.626 | 0 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_10 | 2921 | 1 | 2_3_4 | 2 | 10 | Control | | 0 | 0 | 45432.2 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 2819 | 1 | 1_2_4 | 1 | 13 | Exposed | | 0 | 3423.3 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_5 | 2877 | 1 | 2_3_4 | 2 | 18 | Control | | 0 | 0 | 49759 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_10 | 2856 | 1 | 1_2_3 | 1 | 21 | Control | | 0 | | 39890.5 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_20 | 2855 | 1 | 1_2_4 | 1 | 25 | Exposed | | 0 | 14563.7 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 2814 | 1 | 1_2_4 | 1 | 29 | Exposed | | 0 | 34676.4 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_14 | 2870 | 1 | 1_2_3 | 1 | 33 | Exposed | | 0 | 13134.9 | 0 | 521.4 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+
+
+
+
+
+Github respository (source code)
+--------------------------------
+
+Galaxy Tool Wrappers: https://github.com/computational-metabolomics/dimspy-galaxy/
+DIMSpy package: https://github.com/computational-metabolomics/dimspy/
+
+
+Developers and contributors
+---------------------------
+
+- Ralf Weber (r.j.weber@bham.ac.uk) - University of Birmingham (UK)
+- Martin R. Jones (m.r.jones.1@bham.ac.uk) - University of Birmingham (UK)
+- Thomas Lawson (tnl495@bham.ac.uk) - University of Birmingham (UK)
+
+
+
+
+License
+-------
+DIMSpy is released under the GNU General Public License v3.0 (see `LICENSE file`_)
+
+.. _`LICENSE file`: https://github.com/computational-metabolomics/dimspy-galaxy/blob/master/LICENSE
+
+
+
+
+
diff -r 000000000000 -r 62c4813fbe7a process_scans.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/process_scans.xml Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,370 @@
+
+ - Read, filter and average MS scans
+
+ macros.xml
+
+
+
+ 0.0
+ --min-fraction $mults.min_fraction
+ #else
+ --min-fraction 0.0
+ #end if
+ #if float($mults.rsd_threshold) > 0.0
+ --rsd-threshold $mults.rsd_threshold
+ #end if
+ #if $adv.skip_stitching
+ --skip-stitching
+ #end if
+ #if float($adv.ringing_threshold) > 0.0
+ --ringing-threshold $adv.ringing_threshold
+ #end if
+ #for $mzr in $adv.remove_mz_range
+ --remove-mz-range $mzr.start $mzr.end
+ #end for
+ #if $scan_events.filter == 'true'
+ #for $se in $scan_events.descriptions
+ #if $scan_events.incl_excl == 'include'
+ --include-scan-events $se.start $se.end $se.scan_type
+ #elif $scan_events.incl_excl == 'exclude'
+ --exclude-scan-events $se.start $se.end $se.scan_type
+ #end if
+ #end for
+ #end if
+ --report '$report'
+ &&
+ dimspy hdf5-pls-to-txt
+ --input '$hdf5_file_out'
+ --output .
+ --delimiter $delimiter
+ ]]>
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+
+Process Scans (and SIM stitch)
+==============================
+
+..
+
+----------------
+
+Description
+-----------
+
+Standard DIMS processing workflow: **Process Scans** -> Replicate Filter -> Align Samples -> [Missing values sample filter] -> Blank Filter -> Sample Filter -> Matrix processing -> Statistics
+
+This tool is used to generate a single mass spectral peaklist for each of the data files defined in the ‘Filelist/Samplelist’. The tool extracts mass spectral peaks from a data file (in either .mzML or .RAW format) and then filters these in accordance with user-defined parameter settings. All peaks remaining after filtering are hierarchically clustered in one-dimension, during which pairs of peaks with similar m/z values are grouped together if the difference between their m/z values, when divided by the average of their m/z values and multiplied by 1 x 10\ :sup:`6` \, equates to less-than the user-defined ppm error tolerance.
+
+**IMPORTANT:** when using .mzML files generated using the Proteowizard tool, SIM-type scans will only be treated as spectra if the ‘simAsSpectra’ filter was set to true during the conversion process, e.g.:
+
+*msconvert.exe example.raw* **--simAsSpectra** *--64 --zlib --filter "peakPicking true 1-”*
+
+-----------------
+
+
+Parameters
+----------
+
+***.mzml or *.raw files** (REQUIRED) - use one of the following inputs:
+
+ * **Single or multiple .mzML or .raw file**
+
+ * **Data collection** - use this option if .mzml or .raw files are contained within a Galaxy dataset collection. Dataset collections may be generated within the Galaxy environment.
+
+ * **Zip file** from history - use this option if you have uploaded a \*.zip directory containing \*.mzML files (.raw files are not supported).
+
+
+**Filelist / Samplelist** (HIGHLY RECOMMENDED) - a table containing **filename** and **classLabel** information for each experimental sample. These column headers MUST be included in the first row of the table.
+
+For a standard DIMS experiment, users are advised to also include the following additional columns in order to ensure their data remains compatible with future versions of the dimspy processing pipeline:
+
+ * **injectionOrder** - integer values ranging from 1 to i, where i is the total number of independent infusions performed as part of a DIMS experiment. e.g. if a study included 20 samples, each of which was injected as four independent replicates, there would be at least 20 * 4 injections, so i = 80 and the range for injection order would be from 1 to 80 in steps of 1.
+
+ * **replicate** - integer value from 1 to r, indicating the order in which technical replicates of each study sample were injected in to the mass spectrometer, e.g. if study samples were analysed in quadruplicate, r = 4 and integer values are accordingly 1, 2, 3, 4.
+
+ * **batch** - integer value from 1 to b, where b corresponds to the total number of batches analysed under define analysis conditions, for any given experiment. e.g. : if 4 independent plates of polar extracts were analysed in the positive ionisation mode, then valid values for batch are 1, 2, 3 and 4.
+
+ * **NOTE**: for DIMS experiments, “batch” is synonymous with plate, i.e. each independent plate analysed under a given analytical configuration may be considered an individual “batch”.
+
+ This file:
+
+ * must be uploaded to (or be accessible to) the active Galaxy history in order to allow for its selection in the Filelist / Samplelist drop-down menu. The file list / sample list may be created in .txt format, however, when imported in to the active Galaxy history, users must ensure to select ‘.tabular’ format.
+
+ * may include additional columns, e.g. additional metadata relating to study samples. Ensure that columns names do not conflict with existing column names.
+
+|
+
+@example_filelist@
+
+|
+
+**Function to calculate the noise from each scan** (REQUIRED; default = **median**) - toggle requiring selection of one option from the drop-down menu to indicate the preferred algorithm to apply for spectral noise calculation. The following options are available:
+
+ * **Median** - the median of all peak intensities within a given file is used as the noise value. This simplistic approach to estimating noise may be suitable for spectra with many low abundant features, but it is generally not recommended for use when spectra contain relatively few low-abundant peaks e.g. MS2 spectra.
+
+ * **Mean** - the unweighted mean average of all peak intensities within a given file is used as the noise value. This simplistic approach to estimating noise may be suitable for spectra with many low abundant features, but it is generally not recommended for use when spectra contain relatively few low-abundant peaks e.g. MS2 spectra.
+
+ * **Mean absolute deviation (MAD)** - the noise value is set as the mean of the absolute differences between peak intensities and the mean peak intensity (calculated across all peak intensities within a given file).
+
+ * **Xcalibur** - the noise value is calculated using the proprietary algorithms contained in Thermo Fisher Scientific’s reader libdrary. This option should only be applied when you are processing .RAW files.
+
+|
+
+**Signal-to-noise ratio (SNR) threshold** (REQUIRED; default = 3.0) - a numerical value from 0 upwards.
+
+Peaks with a signal-to-noise ratio (SNR) less-than or equal-to this value will be removed from the output peaklist. In the comprehensive peaklist output (.tsv-formatted), peaks with a SNR below the user-defined threshold will have a ‘0’ in the ‘snr-flag’ column, which indicates that they should be ignored in downstream processing procedures. Peaks with a SNR exceeding the user-defined cutoff will have a ‘1’ in the ‘snr-flag’ column.
+
+|
+
+**Filter specific scan windows or scan events?** (OPTIONAL; default = **No**) - a boolean toggle where:
+
+ * **No** - do not perform scan event filtering;
+
+ * **Yes** - filter specific scan events
+
+ * when selected, users must specify whether to 'Exclude' or 'Include' specific scan events. This can be useful if, for example, a user wishes to run the Process Scans tool on only a subset of scan types collected in each file. e.g. some SIM stitch acquisitions may be initiated with an initial 30 second stabilisation period, during which full-scan data are acquired. This full-scan data can be excluded from further consideration by using the ‘exclude’ toggle.
+
+ * Included or excluded scan events must be fully defined by the user, else ALL scan events will be included. To do so:
+ * Click the '+ Description' button and insert the start and stop m/z values for the scan event to be included/excluded..
+ * Select the 'scan type' to be filtered. Options are: 'Full scan' or 'SIM scan'
+ * Click '+ Description' to 'Exclude/Include' an additional scan event.
+
+|
+
+**Show options for multiple scans** (OPTIONAL)
+
+ * **Minimum number of scans required for each m/z window or event within a raw/mzML data file** (default = 1) - A positive integer equal-to or greater-than 1 that specifies the number of times a given scan event must occur in a given file in order for this scan event to be included in downstream processing steps and in the output .tsv-formatted peaklist.
+
+ * **ppm error tolerance** (default = 2.0) - A positive numerical value equal-to or greater-than zero. This option impacts the clustering of peaks extracted from an input file. If the mass-to-charge ratios of two peaks, when divided by the average of their mass-to-charge ratios and then multiplied by 1 × 106, is equal-to or less-than this user-defined value, then these peaks are clustered together as a single peak. Clustering is applied across all replicates of a given scan event type i.e. with a given input file, all peaks detected in the three replicates of a 50-400 m/z scan event would undergo assessment for the need for clustering.
+
+ * **Minimum fraction (i.e. percentage; default = 0, i.e. skip) of scans a peak has to be present in** - A numerical value from 0 to 1 that specifies the minimum proportion of scans a given mass spectral peak must be detected in, in order for it to be kept in the output peaklist. Here, scans refers to replicates of the same scan event type, i.e. if set to 0.33, then a peak would need to be detected in at least 1 of the 3 replicates of a given scan event type. The ppm error specified by the user will significantly impact which peaks fulfil this criteria.
+
+ * **Relative standard deviation threshold** (default = 0, i.e. skip) - A numerical value equal-to or greater-than 0. If greater than 0, then peaks whose intensity values have a percent relative standard deviation (otherwise termed the percent coefficient of variation) greater-than this value are excluded from the output peaklist.
+
+|
+
+**Show advanced options** (OPTIONAL)
+
+ * **Skip SIM-stitching** (REQUIRED; default = **No**) - a boolean toggle where:
+
+ * **No** - perform SIM stitching
+
+ * **Yes** - skip the processing step where (SIM) windows are 'stitched' or 'joined' together. Use this option if you would like to process individual scan/SIM windows (events/ranges) without 'stitching' them.
+
+ * **Remove m/z range(s)** (OPTIONAL) - this option allows for specific regions of the output peak matrices to be deleted by the user - this option may be useful for removing sections of a spectrum known to correspond to system noise peaks.
+
+ * **Start m/z of removal range** - a positive numerical value corresponding to the lowest m/z value in the spectral region to be removed.
+
+ * **End m/z of removal range** - a positive numerical value corresponding to the highest m/z value in the spectral region to be removed (must be greater than the ‘start m/z of removal range’).
+
+ * **Relative intensity threshold used to remove ringing artefacts** (OPTIONAL) - Fourier transform-based mass spectra often contain peaks (ringing artefacts) around spectral features arising from detection of charged, gas-phase bio-molecules.
+
+ * A positive numerical value indicating the required relative intensity a peak must exceed (with reference to the largest peak in a cluster of peaks) in order to be retained.
+
+----------------------------------
+
+
+Output file(s)
+--------------
+
+|
+
+The Process scans (and SIM stitch) tool will output three file types:
+
+1) **A HDF5 file** containing the processed peaklists
+
+2) **A processed peaklist**, presented in tabular format, for each study sample specified in the filelist/samplelist. Each row corresponds to a single peak. Where multiple peaks were grouped together during the hierarchical clustering process, each peaklist metric constitutes an average of the groups’ values. Metrics included in the peaklist are:
+
+@help_columns_peaklist@
+
+@example_peaklist@
+
+|
+
+3) **A tabular “report” file** that details, for each scan event processed in each file:
+
+ * Scan range of scan event
+
+ * Scan number of scan event
+
+ * Number of peaks detected in scan event
+
+ * Median RSD of peaks detected in each scan event type (only applied if number of scans for a given scan event is ]]> 1
+
+-----------------------------------
+
+@github_developers_contributors@
+@license@
+
+RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights reserved. **Using this galaxy tool implies the acceptance of the RawFileReader** `license terms`_.
+
+.. _`license terms`: https://github.com/computational-metabolomics/dimspy-galaxy/blob/master/tools/dimspy/RawFileReaderLicense.md
+
+|
+
+
+
+
+
+
diff -r 000000000000 -r 62c4813fbe7a test-data/MTBLS79_mzml_triplicates.zip
Binary file test-data/MTBLS79_mzml_triplicates.zip has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep01_262.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262.mzML Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,159 @@
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diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep01_262.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,499 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
+97.0050038629 24371.8476562 10.2138983463 1 0.1 nan 1.0 1.0 1 0 0
+98.9955018467 82339.6554688 34.2217993561 10 1.0 6.92819640371 10.0 1.0 1 1 1
+101.752289053 26659.7988281 11.3852899456 1 0.1 nan 1.0 1.0 1 0 0
+101.753170732 27749.7890625 11.6295460489 1 0.1 nan 1.0 1.0 1 0 0
+101.760001089 27966.8964844 12.0169301401 1 0.1 nan 1.0 1.0 1 0 0
+101.760785449 27373.5214844 10.900619804 1 0.1 nan 1.0 1.0 1 0 0
+101.761942982 31181.6132812 13.3163686068 1 0.1 nan 1.0 1.0 1 0 0
+101.762415519 29687.0507812 11.8219080382 1 0.1 nan 1.0 1.0 1 0 0
+101.762823343 33850.9179688 14.186443307 1 0.1 nan 1.0 1.0 1 0 0
+101.763862658 24648.4902344 10.1551295314 1 0.1 nan 1.0 1.0 1 0 0
+101.769632024 30046.4433594 12.9104783225 1 0.1 nan 1.0 1.0 1 0 0
+101.770656275 29317.1523438 12.0786091445 1 0.1 nan 1.0 1.0 1 0 0
+101.771230198 26653.9208984 11.1798351166 2 0.2 12.3745639478 2.0 1.0 1 0 0
+101.771924703 28194.547526 11.6732716145 3 0.3 12.9357310009 3.0 1.0 1 0 0
+101.77247223 34544.1826172 14.3379527656 2 0.2 12.9547876966 2.0 1.0 1 0 0
+101.773679514 25715.6894531 10.5357634836 1 0.1 nan 1.0 1.0 1 0 0
+101.773953634 30085.4492188 12.417921349 1 0.1 nan 1.0 1.0 1 0 0
+101.774167342 26579.9921875 11.0441488074 2 0.2 5.16123631347 2.0 1.0 1 0 0
+101.774444231 29461.8509115 12.0906833959 3 0.3 20.528388653 3.0 1.0 1 0 0
+101.774765704 27428.7265625 11.5314577636 1 0.1 nan 1.0 1.0 1 0 0
+101.775561023 24917.1816406 10.4206324468 2 0.2 2.75965479961 2.0 1.0 1 0 0
+101.776071685 29167.1809896 12.3954657742 3 0.3 23.4812227967 3.0 1.0 1 0 0
+101.776393302 28083.9746094 11.6515532862 2 0.2 4.85365856211 2.0 1.0 1 0 0
+101.776905074 26652.5761719 11.3388946781 2 0.2 11.7068108415 2.0 1.0 1 0 0
+101.777138532 32581.8847656 13.9143662495 1 0.1 nan 1.0 1.0 1 0 0
+101.777438306 28769.8789062 12.0600745322 4 0.4 9.13554703544 4.0 1.0 1 0 0
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep01_262_2_263_3_264.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262_2_263_3_264.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,436 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep01_262_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262_scan5.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,16 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep02_263.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263.mzML Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,159 @@
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diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep02_263.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,511 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep02_263_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263_scan5.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,16 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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+156.042166366 644582.6875 234.598561741 1 1.0 nan 1.0 1.0 1 1 1
\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep03_264.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264.mzML Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,159 @@
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diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep03_264.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,521 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
+98.9954997246 85420.5765625 31.7500402338 10 1.0 7.05084168152 10.0 1.0 1 1 1
+101.75139692 28253.2851562 10.127417772 1 0.1 nan 1.0 1.0 1 0 0
+101.756447902 26853.5292969 10.2665688721 1 0.1 nan 1.0 1.0 1 0 0
+101.756740955 31525.3886719 12.052701544 1 0.1 nan 1.0 1.0 1 0 0
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC17_rep03_264_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264_scan5.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,16 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC18_rep01_280.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep01_280.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,546 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag rsd_flag flags
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC18_rep02_281.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep02_281.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,502 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_QC18_rep03_282.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep03_282.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,516 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_S01_average.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_S01_average.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,238 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch04_S01_rep01_247_2_248_3_249.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_S01_rep01_247_2_248_3_249.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,238 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/batch_04_QC18_mzml_triplicate.zip
Binary file test-data/batch_04_QC18_mzml_triplicate.zip has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/filelist_merge.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_merge.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,14 @@
+filename classLabel
+batch04_B02_rep01_301.mzML blank
+batch04_B02_rep02_302.mzML blank
+batch04_B02_rep03_303.mzML blank
+batch04_S01_rep01_247.mzML sample
+batch04_S01_rep02_248.mzML sample
+batch04_S01_rep03_249.mzML sample
+batch04_QC17_rep01_262.mzML QC
+batch04_QC17_rep02_263.mzML QC
+batch04_QC17_rep03_264.mzML QC
+batch04_QC18_rep01_280.mzML QC
+batch04_QC18_rep02_281.mzML QC
+batch04_QC18_rep03_282.mzML QC
+
diff -r 000000000000 -r 62c4813fbe7a test-data/filelist_mzml_QC17_triplicate.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_mzml_QC17_triplicate.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,5 @@
+filename replicate injectionOrder classLabel
+batch04_QC17_rep01_262.mzML 1 1 QC
+batch04_QC17_rep02_263.mzML 2 2 QC
+batch04_QC17_rep03_264.mzML 3 3 QC
+
diff -r 000000000000 -r 62c4813fbe7a test-data/filelist_mzml_triplicates.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_mzml_triplicates.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,10 @@
+filename replicate injectionOrder classLabel
+batch04_B02_rep01_301.mzML 1 1 blank
+batch04_B02_rep02_302.mzML 2 2 blank
+batch04_B02_rep03_303.mzML 3 3 blank
+batch04_QC17_rep01_262.mzML 1 4 QC
+batch04_QC17_rep02_263.mzML 2 5 QC
+batch04_QC17_rep03_264.mzML 3 6 QC
+batch04_S01_rep01_247.mzML 1 7 sample
+batch04_S01_rep02_248.mzML 2 8 sample
+batch04_S01_rep03_249.mzML 3 9 sample
diff -r 000000000000 -r 62c4813fbe7a test-data/merged_01.h5
Binary file test-data/merged_01.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/merged_02.h5
Binary file test-data/merged_02.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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132.076101717 132.076671348 132.077202011 132.077992635 132.078371418 132.10124611 132.101899697 133.034572295 133.073124466 133.073801709 133.078935658 133.079460494 133.080118687 133.080632528 133.085244134 133.08588551 133.100506766 133.101138251 133.105278546 134.080996946 134.986830233 134.996465421 135.002862414 135.044024062 135.079258734 135.079764229 135.08038938 135.08097732 135.100884718 135.101532646 135.116137118 135.116787748 136.021508699 136.04691347 136.047429382 136.048119883 136.048697166 136.061765976 136.073251744 136.083096309 136.083761924 136.940051855 137.029491761 137.045065286 137.045773739 137.056596193 137.057269511 137.058997556 137.059672042 137.094876372 137.095391733 137.096043901 137.096633067 137.132444496 138.091309182 138.099413241 139.015603989 139.036530811 139.072917036 139.074630285 139.075322774 139.111014214 139.111701664 140.066921905 140.067478979 140.06819156 140.068751041 140.106954463 140.115061283 141.015855767 141.05218138 141.071577375 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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_compr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,10 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_rmbs.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_rmbs.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,3 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_compr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,11 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_mv.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mv.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,3 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mz.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,238 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_mz_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mz_compr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,897 @@
+mz present occurrence purity rsd_all blank_flag fraction_flag flags batch04_B02_rep01_301_2_302_3_303 batch04_QC17_rep01_262_2_263_3_264 batch04_S01_rep01_247_2_248_3_249
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_within.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_within.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_bf_sf_within_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_within_compr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,11 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_mz.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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+batch04_S01_rep01_247_2_248_3_249 0.0 0.0 0.0 0.0 98.9954985809 0.0 0.0 0.0 0.0 101.777300408 0.0 0.0 0.0 103.038951206 0.0 104.106969562 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 112.05230127 0.0 0.0 0.0 114.066183717 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 118.086254325 0.0 0.0 0.0 0.0 0.0 123.013846528 0.0 0.0 0.0 0.0 126.021940468 0.0 0.0 128.010842465 128.994852728 0.0 0.0 0.0 130.049222294 130.049876497 0.0 0.0 131.009840858 131.010519286 131.018941789 0.0 0.0 0.0 132.074588333 132.075015393 132.075577059 132.076109099 132.07666587 132.077192467 132.077966831 132.078371418 132.101249828 132.101909513 133.03458242 133.073131884 133.073798826 133.078936148 133.079469793 133.080112353 133.080628397 0.0 0.0 0.0 0.0 0.0 134.080984201 0.0 0.0 135.002850005 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 136.04742307 136.048120933 136.048695528 136.061757502 0.0 0.0 0.0 136.940046778 137.029490029 0.0 137.045774736 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 139.015603644 0.0 0.0 0.0 0.0 0.0 0.0 140.066911871 140.067470449 140.068204556 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 143.988083681 0.0 144.101949419 0.0 0.0 0.0 0.0 146.116754363 146.117598873 146.165216189 0.0 147.075011136 147.075627085 147.076369718 147.076979975 0.0 147.112839922 0.0 148.002465779 148.003083125 148.00388917 148.004532676 0.0 148.059620112 148.060469937 148.061106768 148.079814832 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 149.999720327 0.0 150.976841441 152.022107997 0.0 0.0 156.041299644 156.04210896 156.076739228 0.0 0.0 0.0 0.0 0.0 0.0 0.0 160.133200667 161.128435059 162.110698742 162.111590644 162.112344468 162.113092911 163.045143247 163.114842934 163.11582752 0.0 163.976056014 163.976860634 163.977772181 165.97362311 165.975937088 166.086250127 166.950729928 167.021729145 0.0 168.00576552 169.058371327 0.0 170.031627479 170.032607054 0.0 171.036000371 0.0 172.030752313 0.0 0.0 0.0 172.984692285 173.080842158 0.0 0.0 0.0 174.895946971 175.001681537 175.118966325 0.0 176.102979388 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 189.052399827 0.0 0.0 0.0 191.040092185 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 198.084934735 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 200.067008263 200.068348605 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 201.932346714 201.933716782 202.066514029 0.0 202.18018014 203.040083873 203.051218596 203.052602167 203.139045049 203.931846748 0.0 204.056017623 204.120741567 204.121487897 204.122807762 204.123969413 205.055744868 0.0 0.0 0.0 205.124997964 205.126370729 205.154711374 0.0 0.0 206.05532194 206.127316991 207.014279992 207.078225822 0.0 0.0 0.0 0.0 207.988550466 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 210.08734756 210.08912563 0.0 0.0 0.0 0.0 0.0 210.940588306 0.0 210.985283169 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 214.05884903 0.0 0.0 0.0 0.0 0.0 215.069634252 0.0 0.0 0.0 0.0 0.0 0.0 218.137135677 218.138625717 218.186340263 0.0 219.026595149 219.142086543 0.0 0.0 222.029261944 0.0 0.0 0.0 222.988230841 0.0 0.0 0.0 0.0 227.113637246 0.0 0.0 229.152780598 229.154422759 0.0 230.157788325 0.0 232.151176558 232.152361393 232.154026026 0.0 233.157439044 235.065997919 0.0 0.0 238.02274468 0.0 0.0 241.129231877 0.0 242.078628401 242.115013356 0.0 0.0 0.0 0.0 0.0 0.0 245.135416588 245.147334521 245.149273202 0.0 0.0 246.152662683 246.169715055 0.0 0.0 0.0 247.241742171 248.146967314 248.148952839 248.245101195 249.045247385 249.153255588 249.155420706 0.0 250.158789317 250.213845847 0.0 0.0 0.0 0.0 0.0 254.247533265 0.0 0.0 0.0 0.0 256.263179588 257.041913932 257.091126293 0.0 258.109823957 0.0 260.185324487 260.196573871 261.188683931 0.0 262.128216617 262.16460197 0.0 263.145926453 0.0 263.236647595 264.172129098 0.0 0.0 0.0 265.250038827 265.252251512 0.0 266.187758572 266.255625979 0.0 0.0 268.263174107 269.08772033 270.109874888 0.0 270.278807885 0.0 0.0 273.005664599 0.0 0.0 276.1802052 276.229422561 0.0 278.245081352 0.0 0.0 0.0 0.0 0.0 280.263139386 282.276325668 282.278750921 283.282130163 284.294422258 0.0 292.203326231 0.0 0.0 292.2606964 293.071370521 293.206676616 0.0 296.065995008 0.0 0.0 0.0 0.0 298.992898459 0.0 0.0 302.242399929 302.245428093 303.24878925 0.0 304.260752744 304.263413947 0.0 305.264411781 306.219393536 0.0 306.267785589 0.0 0.0 0.0 307.04384865 0.0 308.047278029 308.091094314 0.0 308.235022494 309.042061331 310.047025746 0.0 0.0 0.0 0.0 0.0 0.0 0.0 316.203748156 0.0 316.320989966 317.114987803 318.213669955 318.215895358 318.219220098 0.0 318.240338563 319.222752972 0.0 0.0 320.217554344 320.224871533 0.0 320.229134825 320.231111598 320.234519196 320.241626804 0.0 320.255685787 320.974811232 0.0 321.232197081 321.234786853 321.238176947 0.0 0.0 322.229522709 322.233119641 322.241737876 322.250687978 0.0 323.236505464 0.0 326.948386194 0.0 328.067250132 0.0 0.0 0.0 0.0 0.0 0.0 0.0 332.028913499 0.0 0.0 0.0 334.214273542 0.0 334.250668262 334.271616498 0.0 0.0 336.229929268 0.0 336.948764624 0.0 0.0 338.341734428 0.0 0.0 0.0 0.0 346.047033578 348.070427363 0.0 348.266379527 0.0 350.25403947 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 366.203836216 0.0 0.0 0.0 0.0 368.219386882 0.0 369.22284541 0.0 0.0 370.052050654 0.0 370.247962938 0.0 371.326452665 372.206249404 372.245046935 372.329856912 0.0 374.203335574 0.0 0.0 376.297232822 377.300657538 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 384.206323385 0.0 385.316989323 386.025874125 386.221768966 0.0 0.0 0.0 387.225262028 0.0 387.332638188 0.0 388.218983046 389.222358733 0.0 0.0 0.0 393.358426888 394.279817501 0.0 395.337633663 0.0 396.308075518 396.341053427 0.0 398.020297889 398.032874064 0.0 0.0 0.0 399.357767697 400.157203497 0.0 0.0 407.293469086 408.007897242 408.020525014 408.308085494 408.951037638 0.0 0.0 409.161823425 0.0 0.0 0.0 0.0 411.332645717 413.348274197 413.373403903 414.006828619 0.0 415.156868323 416.084280734 423.981765103 424.281866106 0.0 425.135298418 425.285292567 426.138881798 0.0 427.13386107 427.142901643 0.0 429.262746682 435.061172652 435.330083765 435.988638501 0.0 0.0 443.233520419 0.0 445.248985812 445.98895613 446.252511258 0.0 450.329735454 451.962532082 453.068896429 453.112601976 0.0 0.0 454.04005321 0.0 457.042996949 461.332795944 0.0 461.962809831 0.0 467.23109072 0.0 0.0 469.055315064 0.0 0.0 469.410670251 470.013885023 0.0 471.061108818 471.13283571 0.0 0.0 473.01699606 0.0 0.0 0.0 476.227413736 0.0 0.0 479.335260946 0.0 0.0 483.017348311 483.075303021 0.0 483.944760702 484.311374779 484.323911019 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 499.918623596 0.0 0.0 0.0 0.0 0.0 515.413178882 0.0 0.0 516.416626946 0.0 517.396435931 0.0 0.0 518.250004364 0.0 519.253388986 519.295091303 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 527.183407917 531.408057826 0.0 0.0 0.0 0.0 532.439740342 533.249741237 0.0 0.0 535.520104813 537.378500181 537.394422417 537.535644564 0.0 538.398326377 0.0 0.0 0.0 539.391034626 539.401891838 0.0 0.0 0.0 545.40662442 545.423134445 546.42664666 547.419387343 547.430522439 547.460189893 548.285476369 549.289092376 0.0 550.360250738 553.348894953 553.367647289 0.0 553.376284114 0.0 553.388587287 0.0 554.278572222 554.35522838 554.371478456 0.0 554.393049185 0.0 555.366533294 555.374371686 0.0 556.370106746 0.0 557.073628299 557.09505812 557.501974295 558.505341074 559.151249619 559.517386251 561.535808365 563.551216499 564.554790108 569.345464898 569.363508407 570.367357412 571.361841884
\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_mz_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_mz_compr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,9 @@
+mz missing values tags_injectionOrder tags_classLabel tags_replicates tags_untyped 95.0854867136 96.0477230462 97.0647529114 97.1011384065 98.9954998691 99.0804011767 101.003118017 101.059284262 101.059667337 101.777300408 101.781524007 102.127686063 102.970223555 103.038951206 103.075318834 104.106972509 105.003234195 105.090964311 107.070230246 107.085062328 107.085488315 109.100703053 109.101137314 111.08040236 111.116786045 112.052301283 113.059666808 113.096051485 114.065677969 114.066170487 114.091302909 115.036557299 115.075318293 115.111705216 116.070599012 116.985382141 116.98587154 117.054583395 117.090968646 118.086253653 119.085485311 120.980267261 120.980786531 121.00756219 121.064754009 123.013845316 123.055288913 123.116788199 125.095487802 125.096051948 126.021940468 127.075321735 127.111706998 128.010843476 128.994858336 129.090369007 129.090974735 129.127358602 130.049222294 130.049863468 130.964513436 130.965138358 131.009836808 131.010517825 131.018942036 131.070233883 131.085482301 131.106615399 132.074583988 132.075008963 132.075567318 132.076101717 132.076671348 132.077202011 132.077992635 132.078371418 132.10124611 132.101899697 133.034572295 133.073124466 133.073801709 133.078935658 133.079460494 133.080118687 133.080632528 133.085244134 133.08588551 133.100506766 133.101138251 133.105278546 134.080996946 134.986830233 134.996465421 135.002862414 135.044024062 135.079258734 135.079764229 135.08038938 135.08097732 135.100884718 135.101532646 135.116137118 135.116787748 136.021508699 136.04691347 136.047429382 136.048119883 136.048697166 136.061765976 136.073251744 136.083096309 136.083761924 136.940051855 137.029491761 137.045065286 137.045773739 137.056596193 137.057269511 137.058997556 137.059672042 137.094876372 137.095391733 137.096043901 137.096633067 137.132444496 138.091309182 138.099413241 139.015603989 139.036530811 139.072917036 139.074630285 139.075322774 139.111014214 139.111701664 140.066921905 140.067478979 140.06819156 140.068751041 140.106954463 140.115061283 141.015855767 141.05218138 141.071577375 141.087852717 141.088567109 141.090252262 141.090971445 141.127355825 142.047430796 142.086228559 142.121881522 142.122604088 142.158992032 142.94808538 143.001525805 143.085493568 143.10588682 143.106624835 143.988083681 144.080733504 144.101942195 144.980789437 145.047092142 145.101135997 145.122261684 146.116764318 146.117593543 146.165212548 146.99644084 147.075026099 147.07563403 147.076381496 147.076979975 147.080407767 147.112840746 147.116791771 148.002470297 148.003082516 148.003895413 148.004529246 148.059020674 148.059628878 148.060463029 148.061104039 148.079812778 149.002478676 149.022503043 149.023281113 149.044827912 149.059672206 149.063819045 149.09606266 149.132443185 149.999720327 150.975955392 150.976840465 152.022107353 152.106952838 155.106635915 156.041293988 156.04209741 156.076741027 156.989754618 157.045485596 158.040247352 158.117532287 158.921989272 159.027720801 159.065165762 160.133198751 161.128432541 162.110690219 162.111590644 162.112377858 162.113089295 163.045136563 163.114854206 163.115822095 163.148118188 163.976056014 163.976865689 163.977780102 165.97362311 165.975937112 166.086251818 166.950728597 167.021727034 167.104235181 168.00575923 169.058369029 169.122302355 170.031627109 170.032608751 170.117542392 171.036000371 171.10155643 172.03075001 172.131391412 172.132189987 172.133058362 172.984687975 173.080840757 173.132465407 173.136536346 174.112454069 174.89594473 175.001680018 175.118963541 175.148114856 176.102979229 177.134608611 179.128465135 180.099485034 181.064781256 183.135542334 184.09440398 186.1488452 187.125928194 188.126027407 188.126982017 188.127958364 189.052399827 189.112130373 189.131443965 189.159733638 191.040098978 191.104244442 191.106642836 191.139020145 191.143026735 191.164168196 193.001987153 193.107326275 193.122293797 193.158657464 194.112909063 194.113937225 194.115013807 194.162041956 195.017597191 195.099164614 195.118489509 195.122688638 195.137953706 195.174329384 196.093111731 196.094365648 196.133188662 196.954419421 197.078436232 197.151198232 197.15359074 198.084934735 198.11005386 198.148826946 198.185230589 199.094085221 199.130443878 199.13285878 199.167928041 199.169182065 199.20565281 200.067015416 200.068336832 200.128114646 200.163168249 200.164421525 200.172596426 200.200872992 201.071723083 201.112137504 201.148516239 201.167861307 201.18489544 201.932346714 201.933718688 202.066511789 202.143739474 202.180178742 203.040079527 203.051224356 203.052583123 203.139034837 203.931844481 204.04214677 204.056007584 204.120741567 204.121476777 204.122881675 204.123967408 205.055741463 205.08591946 205.097182566 205.122293634 205.124995123 205.126369088 205.154711374 205.158691684 205.195062356 206.05531063 206.1273128 207.014274578 207.078225213 207.101570295 207.137952093 207.159083317 207.174339207 207.988550264 207.998291404 208.09441105 208.130805683 208.169561137 209.117232919 209.153584829 209.172945534 209.177406022 209.189980267 210.087340882 210.089121447 210.107509217 210.109927964 210.148859874 210.156956315 210.185237724 210.940588306 210.970069553 210.985281317 211.094097176 211.096498226 211.113409698 211.169225897 212.125679781 212.128118487 212.1644968 213.0671985 213.146104172 213.568883933 214.058850666 214.089621826 214.101814932 214.143778719 214.1801328 214.25290771 215.069634252 215.104251358 215.16417564 216.159420321 217.104653094 217.10704668 217.195075119 218.137147136 218.138617868 218.18633146 219.017655316 219.026587805 219.142081286 219.174338426 220.130795435 222.029254451 222.072488512 222.11007085 222.146462571 222.988227171 224.125710227 226.104758587 226.141172094 226.216351729 227.113639423 228.195607363 228.231982987 229.152780695 229.154420238 229.235339774 230.157792453 231.144938826 232.151182802 232.152363977 232.154032856 232.155655558 233.157441453 235.066006489 236.112634358 236.992211984 238.022752298 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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_as_t.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_t.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,894 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_hdf5_to_txt_comprehensive_snr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_comprehensive_snr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,11 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_hdf5_to_txt_intensity.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_intensity.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,897 @@
+mz present occurrence purity rsd_all blank_flag fraction_flag flags batch04_B02_rep01_301_2_302_3_303 batch04_QC17_rep01_262_2_263_3_264 batch04_S01_rep01_247_2_248_3_249
+missing values 231 0 0
+tags_classLabel blank QC sample
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diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_hdf5_to_txt_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_mz.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/peak_matrix_hdf5_to_txt_snr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_snr.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+mz 98.9954998691 104.106972509 112.052301283 118.086253653 123.013845316 128.010843476 128.994858336 131.009836808 131.010517825 131.018942036 132.074583988 132.075008963 132.075567318 132.076101717 132.076671348 132.077202011 132.077992635 132.10124611 132.101899697 133.073124466 133.073801709 133.078935658 133.079460494 133.080118687 133.080632528 134.080996946 135.002862414 136.047429382 136.048119883 136.048697166 136.061765976 136.940051855 137.029491761 137.045773739 139.015603989 140.066921905 140.067478979 140.06819156 144.101942195 146.116764318 146.117593543 146.165212548 147.075026099 147.07563403 147.076381496 147.112840746 148.002470297 148.003082516 148.003895413 148.004529246 148.059628878 148.060463029 148.061104039 148.079812778 150.976840465 152.022107353 156.041293988 156.04209741 156.076741027 160.133198751 161.128432541 162.110690219 162.112377858 162.113089295 163.045136563 163.114854206 163.115822095 163.976865689 163.977780102 165.975937112 166.086251818 166.950728597 167.021727034 168.00575923 169.058369029 170.031627109 170.032608751 172.03075001 172.984687975 173.080840757 174.89594473 175.001680018 175.118963541 176.102979229 191.040098978 200.067015416 200.068336832 201.933718688 202.066511789 202.180178742 203.040079527 203.051224356 203.052583123 203.931844481 204.056007584 204.121476777 204.122881675 204.123967408 205.055741463 205.124995123 205.126369088 206.05531063 206.1273128 207.014274578 207.078225213 207.988550264 210.087340882 210.089121447 210.985281317 214.058850666 218.137147136 218.138617868 218.18633146 219.026587805 219.142081286 222.029254451 222.988227171 227.113639423 229.152780695 229.154420238 230.157792453 232.151182802 232.152363977 232.154032856 233.157441453 235.066006489 238.022752298 241.129235983 242.078631865 242.115014467 245.13541974 245.147333125 245.149278063 246.152668181 246.169719791 248.146977998 248.148957043 249.045257364 249.153279612 249.155411959 250.158796263 257.041913238 258.109821983 260.185330942 260.196578012 262.128218019 262.164606458 263.145935141 266.187766715 269.087730151 270.109886656 276.180208183 293.071380726 296.06590552 298.992809793 306.21928064 307.043708382 308.047169681 308.090980265 309.041951809 310.046940741 316.203654392 317.114880954 318.215940621 318.219163989 319.222645274 320.217490758 320.234511416 320.974705507 321.234813105 321.238113065 322.23301528 322.241621481 322.250574378 323.236408988 328.067170959 332.028813361 334.214166454 336.229835303 336.948656669 346.046894367 348.070300004 366.203861182 369.222872079 370.052089279 371.326530086 376.29721222 377.300668857 386.025883713 386.221824198 394.27986697 395.33770243 400.157233205 408.007909317 413.348315017 415.156897262 416.084309262 424.281826443 425.135463252 425.28532915 426.138910614 427.133904681 427.142968192 445.249096557 445.988977013 453.112608304 454.040051872 457.043005407 461.332821274 461.962854671 469.410689679 470.013893312 476.227406838 483.075340494 483.944790467 484.323934317 517.396406557 518.25000135 519.253359366 527.183398853 533.249780822 545.423300216 546.426817562 548.28553146 549.289149666 553.348831297 553.367591025 553.376240677 554.355151822 554.371473263 555.366527064 555.37434307 556.370112699 557.095013624 559.151213812 569.363651248 570.367404206
+batch04_B02_rep01_301_2_302_3_303 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12.607746951 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.9315357131 0.0 0.0 0.0 0.0 12.191284193 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.0228681487 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 16.721668907 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 31.8453169498 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+batch04_QC17_rep01_262_2_263_3_264 32.5719724663 12.6735172174 55.1549994333 118.259992552 14.3534456993 16.5659710001 19.3910609118 12.9228752459 49.9544844197 17.018537472 10.8787418419 24.1419717358 125.783713476 593.871970439 6010.39372591 676.667227362 15.2668269025 32.5136486883 112.146596205 11.3145139942 40.9071755672 13.2031550682 45.2277673121 170.179025989 14.1855765574 18.5025573736 30.8909201674 29.2288822853 198.16610213 15.9252608268 22.8404921696 47.6717391341 15.9012382379 88.6451797345 34.3442986531 23.3255065625 70.1001135058 481.515262204 21.8807626857 24.4172426399 140.598889068 12.4130278071 34.2847841946 124.289473561 869.122224227 23.0039969509 15.4921685578 42.087089696 258.637927557 18.5926837652 43.1219828844 268.900264667 19.2751855494 31.4107880482 70.1984897635 36.6034840668 34.7406465976 290.040817918 14.8732859394 33.6976320109 16.3690253998 29.4065133599 1431.88890346 124.103236108 11.8557848057 10.7341803635 83.1408823942 24.5574231178 219.200515336 16.2914188264 24.8393676074 46.9805932827 55.7793322532 24.9971874585 36.5229789092 19.0529025363 191.310965875 13.1645999927 14.3226781301 31.9325909958 21.8457173307 62.0737268744 51.1685300827 33.7054423368 27.8972942011 26.8084656975 178.530357592 71.0994885663 13.4187346902 28.0084346086 68.8393664551 43.3049934893 299.822457953 11.6111408758 18.2494269136 212.538273779 3194.34945778 236.698688635 25.9440408367 35.5755417 232.424501909 22.4490233941 17.7496593286 45.8735725404 15.3769344918 11.2946834848 18.7747295574 13.2392438261 17.1837382516 57.9972003973 33.2248561681 386.219087976 55.661316114 59.891104486 33.8909093421 30.0659234819 31.6725799877 12.2108617279 30.763355909 264.166798787 32.376363531 15.9260901646 65.3927654547 594.733980513 65.1674912943 13.971325204 32.6559408164 19.5766533832 53.2726789888 12.1380073091 28.8499918306 29.5990672246 306.397147564 33.4086217343 70.5601000935 11.3677191703 114.746065992 26.752829553 42.2094994385 439.442747435 36.8327722823 15.863419896 20.5750398925 59.3467554387 13.0461068014 29.0760895847 32.2686006934 38.9709928759 30.9702423414 14.6947831254 11.762308005 11.3280376038 25.8622332498 68.2445173598 18.2415661125 11.2311476171 376.309167703 37.5206953056 53.1965227675 26.3357928708 14.1247618719 18.9859562978 24.3758794894 12.0442116872 175.646338272 30.5748388038 11.4379934706 1582.78733006 46.695148752 17.671470985 261.271100085 88.0412646308 20.6899998473 18.6091410812 15.4198176312 15.758689671 12.4337242067 58.6205708532 53.8245168181 36.963925221 22.646691024 17.7707397017 23.7712708486 49.6964680231 24.4130925933 34.7134995687 210.009255088 44.9502918068 73.1498540546 70.0984494163 14.8018184138 15.8915179116 16.6235699115 12.5259725058 13.0132034445 13.965460015 11.5704977174 220.043221181 659.300284875 42.7227181838 140.707214302 38.7950332252 12.7874836523 25.0623082078 22.388263349 14.9038610086 20.6604820122 11.0263311771 41.2595141661 24.1004117074 19.1870969856 13.0118151987 17.8110101334 16.7136157656 14.2261752696 16.3932057203 32.4563109428 67.7249862558 18.8187124753 18.2962474876 14.4689798908 329.679068158 99.8957760263 121.352079276 38.009714774 41.7780198121 2823.83227642 85.1605921543 19.4339962698 884.458777661 207.675374763 108.969986691 53.2340901707 19.0299005103 14.8620174687 154.679537445 42.921133024
+batch04_S01_rep01_247_2_248_3_249 29.1450101692 11.4029541309 26.6706097673 65.9129785479 12.8361207096 12.5887141682 18.1738870974 12.5029416526 39.2420940643 17.5236947432 14.5521229306 33.7015165238 172.921630576 783.074503416 7890.53014739 908.060331335 19.7999598644 31.0065089557 106.320383274 14.1627966488 48.5067629241 15.4655233304 57.0005637827 220.002640213 20.2645705597 23.6425345661 15.7389691415 22.4742009609 153.800490893 12.9021969764 13.5289343462 35.1791189379 17.8027145046 22.9101033887 29.0717840023 10.4351781971 26.0012626069 162.171595168 20.5234147547 11.7347068919 68.0448555761 15.209643774 35.7072823486 141.614224422 995.488692629 15.3596100852 19.626216186 54.8042362232 332.410853955 27.5707172754 23.0818703511 132.401997754 11.352292313 34.1915179905 52.7082207875 32.6922781816 16.7298237531 129.373547053 12.7332443974 37.6588394362 20.1752219396 32.6255898833 1649.89025387 144.575605326 11.8182139938 11.4577517246 95.4530369747 45.9819102429 392.376498483 28.6812937849 19.6600308029 45.5710384955 65.0245470428 27.6596723274 34.4479945792 26.2370255633 259.109789326 16.9909428614 24.5757517546 45.0510309736 19.7665266095 12.0902301177 29.6325758677 64.4142199996 28.2921152043 23.6056160166 155.109908421 117.512065403 12.7732910828 14.759327 67.4040483492 26.6529754807 176.988021752 17.5671512792 11.8161616815 222.972124841 3525.53976256 263.377489596 22.0258326279 40.9965299845 249.834282356 11.4210228614 18.5953076191 35.3365523063 14.2361444326 11.2876774111 20.9367772161 11.5275722745 14.1466575878 113.357580204 30.4918200742 358.677860537 41.2184943593 44.2327665617 30.9008074552 18.2433951854 32.3166525292 11.7615071479 17.9647800696 161.862502292 19.539131141 16.4229752553 70.8119997843 646.791207011 71.6622317938 11.6676296228 49.6346364686 36.9962397464 42.8220250099 11.5269539356 22.9558739192 27.4410772485 290.575242551 31.6793065631 62.6602968912 11.4656015113 121.121197186 19.1667556434 23.2561335574 223.913527883 19.1146764412 13.0070937558 12.5300643331 84.5048169726 11.9952981643 23.3776659038 21.702191176 54.4286459454 32.5792303817 27.277565931 13.2493745891 14.5218996643 23.3774057332 20.3142241481 14.5305001268 16.8158418665 220.080362075 22.0781658101 30.006752663 16.159203984 15.8490953533 42.2571291115 13.514541111 51.2980983968 395.004885103 68.7928077379 28.6226900936 3628.29618503 31.9664090314 55.4092030284 545.672030518 181.948983687 41.5621679602 31.7855620533 32.1722225497 11.5835913921 11.3845749449 45.2281762965 58.4538694971 33.4367058724 12.9887217159 13.0354007449 13.4972177977 21.05986485 18.2935739723 89.8372157561 106.444029387 23.3553817068 76.6293564426 200.365390026 47.7423326559 66.5581176078 24.915301286 11.3751403225 42.5010621501 15.2219615383 13.6225768138 93.170038069 649.769086575 18.7622178523 137.910560001 38.047406797 12.1897174967 131.518907352 39.1682927832 14.9572361498 25.9559281077 19.2532003976 21.1105985765 54.7118976534 15.1767110975 16.1073993052 12.9750653887 13.6749271877 22.4408723712 24.5162391824 16.3589347091 55.7023528125 16.274560588 12.4047150391 11.2490564201 551.885046616 247.444133255 153.680848731 46.6732912371 37.7174316228 2496.18228347 82.0966312828 17.4906830242 777.190722473 181.653269998 95.7877629621 46.7377488266 14.4233930202 11.5941650138 305.739047439 83.6481389716
\ No newline at end of file
diff -r 000000000000 -r 62c4813fbe7a test-data/pls.h5
Binary file test-data/pls.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/pls_QC18.h5
Binary file test-data/pls_QC18.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/pls_rf.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pls_scan5.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as_bf.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as_bf_rmbs.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as_bf_sf.h5
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diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as_bf_sf_mv.h5
Binary file test-data/pm_as_bf_sf_mv.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/pm_as_bf_sf_within.h5
Binary file test-data/pm_as_bf_sf_within.h5 has changed
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_01.xt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_01.xt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,73 @@
+filename event scans peaks median_rsd
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 125 8.16474487133
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 118 7.91689453929
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 66 7.68607124086
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 59 7.3571823389
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 38 7.81073302387
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 31 7.11304069203
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 45 6.30005138853
+batch04_B02_rep01_301.mzML SIM-Stitch NA 482 7.76858437374
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 128 8.07600991574
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 125 8.03864926779
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 65 7.44888873374
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 61 6.29657260707
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 47 7.01271931319
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 31 7.3500419991
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 43 7.37566447385
+batch04_B02_rep02_302.mzML SIM-Stitch NA 500 7.68715459068
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 123 9.16935154458
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 118 7.55444375891
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [210.00-310.00] 15 66 7.78351619427
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 57 6.27056997549
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 44 8.20380544323
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 32 8.26327800306
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 45 8.21592686599
+batch04_B02_rep03_303.mzML SIM-Stitch NA 485 8.03552677192
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 79 7.03196696794
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 80 7.76766561352
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 61 8.15363335888
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 54 6.06465919921
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 38 6.24970496714
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 19 7.42363265295
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 38 7.08865209918
+batch04_QC17_rep01_262.mzML SIM-Stitch NA 369 7.18546096997
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 77 7.67971252743
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 76 7.40959870023
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 61 8.07007716689
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 53 6.56434715809
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 43 6.01206175751
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 19 6.89479622473
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 41 6.82339923038
+batch04_QC17_rep02_263.mzML SIM-Stitch NA 370 7.32153403689
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 76 7.06684475755
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 77 7.70812724744
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 62 7.27381932537
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 56 6.85168250471
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 44 8.1369518449
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 22 9.04310387911
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 44 8.17119973043
+batch04_QC17_rep03_264.mzML SIM-Stitch NA 381 7.63853989932
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 67 6.9449339373
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [140.00-240.00] 12 74 7.56562141338
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 63 7.25018452732
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 51 6.83402648161
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 46 6.86311688031
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 30 7.56433662729
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 47 7.38328588939
+batch04_S01_rep01_247.mzML SIM-Stitch NA 378 7.20481827147
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 68 7.61402326633
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 74 6.91382809333
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [210.00-310.00] 15 63 7.81020674999
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 52 6.67116706795
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 49 7.47235757299
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 29 9.18092932673
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 50 7.49743321145
+batch04_S01_rep02_248.mzML SIM-Stitch NA 385 7.44772817369
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 70 8.14059659419
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 72 6.70234634239
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 60 8.31220999647
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 51 6.64301911594
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 48 6.5996960655
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 30 7.38454762189
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 50 9.08654743835
+batch04_S01_rep03_249.mzML SIM-Stitch NA 381 7.56306270833
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_02.xt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_02.xt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,25 @@
+filename event scans peaks median_rsd
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 62 9.10679576511
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 66 8.37633825047
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 30 13.8609519301
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 43 11.9950166441
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 32 10.1868114169
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 15 11.2326559481
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 24 14.1641211658
+batch04_QC18_rep01_280.mzML SIM-Stitch NA 272 10.8339327639
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 56 10.022274693
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 47 16.5074895025
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 47 10.32312253
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 46 7.96958465718
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 30 8.39097430939
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 16 9.67349503755
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [490.00-590.00] 12 27 9.46664767552
+batch04_QC18_rep02_281.mzML SIM-Stitch NA 269 10.0625229083
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 69 7.5232876329
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 71 7.71867980771
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 50 7.01093076419
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 49 7.24728641458
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 39 8.26255528557
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 20 8.48394726745
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 41 5.46125101547
+batch04_QC18_rep03_282.mzML SIM-Stitch NA 339 7.33323994646
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_rf_01.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_rf_01.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+name peaks peaks_3oo3 median_rsd_3oo3
+batch04_B02_rep01_301_2_302_3_303 487 421 12.3353334905
+batch04_QC17_rep01_262_2_263_3_264 364 321 7.90853836608
+batch04_S01_rep01_247_2_248_3_249 383 331 5.34421558583
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_rf_02.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_rf_02.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+name peaks peaks_3oo3 median_rsd_3oo3
+batch04_B02_rep01_301_2_302_3_303 487 421 12.3353334905
+batch04_QC17_rep01_262_2_263_3_264 364 321 7.90853836608
+batch04_S01_rep01_247_2_248_3_249 383 331 5.34421558583
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_rf_03.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_rf_03.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,2 @@
+name peaks peaks_3oo3 median_rsd_3oo3
+batch04_QC17_rep01_262_2_263_3_264 15 15 8.60246934744
diff -r 000000000000 -r 62c4813fbe7a test-data/report_pls_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_scan5.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+filename event scans peaks median_rsd
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
diff -r 000000000000 -r 62c4813fbe7a test-data/sample_list_after_bf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sample_list_after_bf.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,3 @@
+filename injectionOrder replicates classLabel
+batch04_QC17_rep01_262_2_263_3_264 4 1_2_3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1_2_3 sample
diff -r 000000000000 -r 62c4813fbe7a test-data/sample_list_after_mv_filter.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sample_list_after_mv_filter.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,3 @@
+filename classLabel
+batch04_QC17_rep01_262_2_263_3_264 QC
+batch04_S01_rep01_247_2_248_3_249 sample
diff -r 000000000000 -r 62c4813fbe7a test-data/samplelist_1.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/samplelist_1.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+filename injectionOrder replicates classLabel
+batch04_B02_rep01_301_2_302_3_303 1 1_2_3 blank
+batch04_QC17_rep01_262_2_263_3_264 4 1_2_3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1_2_3 sample
diff -r 000000000000 -r 62c4813fbe7a test-data/samplelist_2.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/samplelist_2.txt Sat Apr 11 16:48:19 2020 -0400
@@ -0,0 +1,4 @@
+filename injectionOrder replicates classLabel
+batch04_B02_rep01_301_2_302_3_303 1 1_2_3 blank
+batch04_QC17_rep01_262_2_263_3_264 4 1_2_3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1_2_3 sample