Mercurial > repos > cstrittmatter > ss2v110

comparison SeqSero2.egg-info/PKG-INFO @ 10:e6437d423693 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
author cstrittmatter
date Fri, 01 May 2020 13:30:43 -0400
parents
children
comparison
equal deleted inserted replaced
9:43f6b7f6ebb3 10:e6437d423693
1 Metadata-Version: 1.1
2 Name: SeqSero2
3 Version: 1.1.1
4 Summary: Salmonella serotyping
5 Home-page: https://github.com/denglab/SeqSero2/
6 Author: Shaokang Zhang, Hendrik C Den-Bakker and Xiangyu Deng
7 Author-email: zskzsk@uga.edu, Hendrik.DenBakker@uga.edu, xdeng@uga.edu
8 License: GPLv2
9 Description: # SeqSero2 v1.1.1
10 Salmonella serotype prediction from genome sequencing data.
11
12 Online version: http://www.denglab.info/SeqSero2
13
14 # Introduction
15 SeqSero2 is a pipeline for Salmonella serotype prediction from raw sequencing reads or genome assemblies
16
17 # Dependencies
18 SeqSero2 has three workflows:
19
20 (A) Allele micro-assembly (default). This workflow takes raw reads as input and performs targeted assembly of serotype determinant alleles. Assembled alleles are used to predict serotype and flag potential inter-serotype contamination in sequencing data (i.e., presence of reads from multiple serotypes due to, for example, cross or carryover contamination during sequencing).
21
22 Allele micro-assembly workflow depends on:
23
24 1. Python 3;
25
26 2. Biopython 1.73;
27
28 3. [Burrows-Wheeler Aligner v0.7.12](http://sourceforge.net/projects/bio-bwa/files/);
29
30 4. [Samtools v1.8](http://sourceforge.net/projects/samtools/files/samtools/);
31
32 5. [NCBI BLAST v2.2.28+](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);
33
34 6. [SRA Toolkit v2.8.0](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);
35
36 7. [SPAdes v3.9.0](http://bioinf.spbau.ru/spades);
37
38 8. [Bedtools v2.17.0](http://bedtools.readthedocs.io/en/latest/);
39
40 9. [SalmID v0.11](https://github.com/hcdenbakker/SalmID).
41
42
43 (B) Raw reads k-mer. This workflow takes raw reads as input and performs rapid serotype prediction based on unique k-mers of serotype determinants.
44
45 Raw reads k-mer workflow (originally SeqSeroK) depends on:
46
47 1. Python 3;
48 2. [SRA Toolkit](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software) (optional, just used to fastq-dump sra files);
49
50
51 (C) Genome assembly k-mer. This workflow takes genome assemblies as input and the rest of the workflow largely overlaps with the raw reads k-mer workflow
52
53 # Installation
54 ### Conda
55 To install the latest SeqSero2 Conda package (recommended):
56 ```
57 conda install -c bioconda seqsero2=1.1.1
58 ```
59 ### Git
60 To install the SeqSero2 git repository locally:
61 ```
62 git clone https://github.com/denglab/SeqSero2.git
63 cd SeqSero2
64 python3 -m pip install --user .
65 ```
66 ### Other options
67 Third party SeqSero2 installations (may not be the latest version of SeqSero2): \
68 https://github.com/B-UMMI/docker-images/tree/master/seqsero2 \
69 https://github.com/denglab/SeqSero2/issues/13
70
71
72 # Executing the code
73 Make sure all SeqSero2 and its dependency executables are added to your path (e.g. to ~/.bashrc). Then type SeqSero2_package.py to get detailed instructions.
74
75 Usage: SeqSero2_package.py
76
77 -m <string> (which workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a)
78
79 -t <string> (input data type, '1' for interleaved paired-end reads, '2' for separated paired-end reads, '3' for single reads, '4' for genome assembly, '5' for nanopore fasta, '6'for nanopore fastq)
80
81 -i <file> (/path/to/input/file)
82
83 -p <int> (number of threads for allele mode, if p >4, only 4 threads will be used for assembly since the amount of extracted reads is small, default=1)
84
85 -b <string> (algorithms for bwa mapping for allele mode; 'mem' for mem, 'sam' for samse/sampe; default=mem; optional; for now we only optimized for default "mem" mode)
86
87 -d <string> (output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number)
88
89 -c <flag> (if '-c' was flagged, SeqSero2 will only output serotype prediction without the directory containing log files)
90
91 -n <string> (optional, to specify a sample name in the report output)
92
93 -s <flag> (if '-s' was flagged, SeqSero2 will not output header in SeqSero_result.tsv)
94
95 --check <flag> (use '--check' flag to check the required dependencies)
96
97 -v, --version (show program's version number and exit)
98
99
100 # Examples
101 Allele mode:
102
103 # Allele workflow ("-m a", default), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
104 SeqSero2_package.py -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
105
106 K-mer mode:
107
108 # Raw reads k-mer ("-m k"), for separated paired-end raw reads ("-t 2")
109 SeqSero2_package.py -m k -t 2 -i R1.fastq.gz R2.fastq.gz
110
111 # Genome assembly k-mer ("-t 4", genome assemblies only predicted by the k-mer workflow, "-m k")
112 SeqSero2_package.py -m k -t 4 -i assembly.fasta
113
114 # Output
115 Upon executing the command, a directory named 'SeqSero_result_Time_your_run' will be created. Your result will be stored in 'SeqSero_result.txt' in that directory. And the assembled alleles can also be found in the directory if using "-m a" (allele mode).
116
117
118 # Citation
119 Zhang S, Den-Bakker HC, Li S, Dinsmore BA, Lane C, Lauer AC, Fields PI, Deng X.
120 SeqSero2: rapid and improved Salmonella serotype determination using whole genome sequencing data.
121 **Appl Environ Microbiology. 2019 Sep; 85(23):e01746-19.** [PMID: 31540993](https://aem.asm.org/content/early/2019/09/17/AEM.01746-19.long)
122
123 Zhang S, Yin Y, Jones MB, Zhang Z, Deatherage Kaiser BL, Dinsmore BA, Fitzgerald C, Fields PI, Deng X.
124 Salmonella serotype determination utilizing high-throughput genome sequencing data.
125 **J Clin Microbiol. 2015 May;53(5):1685-92.** [PMID: 25762776](http://jcm.asm.org/content/early/2015/03/05/JCM.00323-15)
126
127 Keywords: Salmonella serotyping bioinformatics WGS
128 Platform: UNKNOWN
129 Classifier: Development Status :: 3 - Alpha
130 Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
131 Classifier: Programming Language :: Python :: 3
132 Classifier: Topic :: Text Processing :: Linguistic