<?xml version="1.0"?>
<tool id="mageck_pathway" name="MAGeCK pathway" version="@VERSION@" >
    <description>- given a ranked gene list, test whether one pathway is enriched</description>
    <macros>
        <import>mageck_macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <expand macro="version" />
    <command detect_errors="exit_code"><![CDATA[

mageck pathway

--gene-ranking '$gene_ranking'
--gmt-file '$gmt_file'
-n sample1

#if $adv.single_ranking:
    --single-ranking
#end if
--method $adv.method
--sort-criteria  $adv.sort_criteria
--ranking-column $adv.ranking_column
--ranking-column-2 $adv.ranking_column2
--pathway-alpha $adv.pathway_alpha
--permutation $adv.permutation

    ]]></command>
    <inputs>
        <param name="gene_ranking" argument="--gene-ranking" type="data" format="tabular" label="Gene Ranking file" help="The gene ranking file generated by the gene test step. Only one enrichment comparison will be performed." />
        <param name="gmt_file" argument="--gmt-file" type="data" format="tabular" label="Pathway GMT file" help="The pathway file in GMT format. See Help below for more information" />

        <section name="adv" title="Advanced Options">
            <param name="single_ranking" argument="--single-ranking" type="boolean" truevalue="--single-ranking" falsevalue="" checked="false" optional="true"
                label="Single ranking file"
                help="The provided file is a (single) gene ranking file, either positive or negative selection. Only one enrichment comparison will be performed. Default: No" />
            <param name="method" argument="--method" type="select" label="Method for testing pathway enrichment" >
                <option value="gsea" selected="True">GSEA</option>
                <option value="rra">RRA</option>
            </param>
            <expand macro="sort_criteria" />
            <param name="ranking_column" argument="--ranking-column" type="data_column" data_ref="gene_ranking" value="2" optional="true"
                label="Gene Summary file column" help="Column number or label in gene summary file for gene ranking; can be either an integer of column number, or a string of column label. Default: 2 (the 3rd column)" />
            <param name="ranking_column2" argument="--ranking-column-2" type="data_column" data_ref="gene_ranking" value="8" optional="true"
                label="Gene Summary file column" help="Column number or label in gene summary file for gene ranking; can be either an integer of column number, or a string of column label. This option is used to determine the column for positive selections and is disabled if --single-ranking is specified. Default: 8 (the 9th column)" />
            <param name="pathway_alpha" argument="--pathway-alpha" type="float" min="0" value="0.25" optional="true"
                label="Alpha value for RRA pathway enrichment" help="The default alpha value for RRA pathway enrichment. Default: 0.25" />
            <param argument="--permutation" type="integer" min="0" value="1000" optional="true" label="Permutation number for GSEA" help="Default: 1000" />
            <param name="out_log" type="boolean" truevalue="True" falsevalue="" checked="false"
                label="Output Log file" help="This file includes the logging information during the execution. Default: No" />
        </section>

    </inputs>

    <outputs>
        <data name="pathway_summary" format="tabular" from_work_dir="*.pathway_summary.txt" label="${tool.name} on ${on_string}: Pathway Summary" />
        <data name="log" format="tabular" from_work_dir="*.log" label="${tool.name} on ${on_string}: Log" >
            <filter>adv['out_log'] is True</filter>
        </data>
    </outputs>
    <tests>
        <test><!-- Ensure MAGeCK's demo1 test works -->
            <param name="gene_ranking" ftype="tabular" value="out.test.gene_summary.txt"  />
            <param name="gmt_file" ftype="tabular" value="in.mageckQC.gmt" />
            <param name="ranking_column" value="2" />
            <param name="out_log" value="True"/>
            <output name="pathway_summary" value="out.pathway.pathway_summary.txt" />
            <output name="log" value="out.pathway.log.txt" compare="sim_size" />
        </test>
    </tests>

    <help><![CDATA[
.. class:: infomark

**What it does**

MAGeCK pathway can also invoke robust ranking aggregation (RRA) to test if a pathway is enriched in one particular gene ranking, see **More Information** below.

-----

**Inputs**

**Gene Ranking files**

A gene ranking file is required as input and can be produced using **mageck test**. An example of the gene ranking file (gene summary file) is as follows:

======= ======= ============= =============== =========== ============ ================= =========== ============= =============== =========== ============ ================= ===========
**id**  **num** **neg|score** **neg|p-value** **neg|fdr** **neg|rank** **neg|goodsgrna** **neg|lfc** **pos|score** **pos|p-value** **pos|fdr** **pos|rank** **pos|goodsgrna** **pos|lfc**
------- ------- ------------- --------------- ----------- ------------ ----------------- ----------- ------------- --------------- ----------- ------------ ----------------- -----------
ESPL1   12      6.4327e-10    7.558e-06       7.9e-05      1           -2.35             11          0.99725       0.99981         0.999992    615          0                 -0.07
RPL18   12      6.4671e-10    7.558e-06       7.9e-05      2           -2.12             11          0.99799       0.99989         0.999992    620          0                 -0.32
CDK1    12      2.6439e-09    7.558e-06       7.9e-05      3           -1.93             12          1.0           0.99999         0.999992    655          0                 -0.12
======= ======= ============= =============== =========== ============ ================= =========== ============= =============== =========== ============ ================= ===========


**Pathway file**

MAGeCK pathway also requires a pathway file in GMT format. The GMT (Gene Matrix Transposed) file format is a tab delimited file format that describes gene sets and is consistent with the `GMT file in Gene Set Enrichment Analysis (GSEA)`_. In the GMT format, each row represents a gene set, with the first column containing the gene set name, and the second column containing a description for the gene set, followed by the names or ids of the genes in the gene set. You can download different GMT pathway files directly from the `GSEA MSigDB database`_.  An example of the GMT format is as follows:

=============  =============================================================  =======================
Gene Set Name  Description                                                    Genes
-------------  -------------------------------------------------------------  -----------------------
KEGG_RIBOSOME  http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_RIBOSOME  RPL35   RPL23   RPL3...
=============  =============================================================  =======================

-----

**Outputs**

**Pathway summary file**

An example of the pathway summary output file is as follows:

============= ======= ============= =========== =============== =========== ============ ================ ============= ============= =========== =============== =========== ============ ================ ===========
**id**        **num** **neg|score** **neg|rra** **neg|p-value** **neg|fdr** **neg|rank** **neg|goodgene** **neg|lfc**   **pos|score** **pos|rra** **pos|p-value** **pos|fdr** **pos|rank** **pos|goodgene** **pos|lfc**
------------- ------- ------------- ----------- --------------- ----------- ------------ ---------------- ------------- ------------- ----------- --------------- ----------- ------------ ---------------- -----------
KEGG_RIBOSOME 88      1             0           0               0           1            0                0             1             0           0               0               1   00
============= ======= ============= =========== =============== =========== ============ ================ ============= ============= =========== =============== =========== ============ ================ ===========

The contents of each column is as follows:

* **id**  Gene ID
* **num** The number of targeting sgRNAs for each gene
* **neg|score** The RRA lo value of this gene in negative selection
* **neg|p-value** The raw p-value (using permutation) of this gene in negative selection
* **neg|fdr** The false discovery rate of this gene in negative selection
* **neg|rank**  The ranking of this gene in negative selection
* **neg|goodsgrna** The number of "good" sgRNAs, i.e., sgRNAs whose ranking is below the alpha cutoff (determined by the --gene-test-fdr-threshold option), in negative selection.
* **neg|lfc** The log fold change of this gene in negative selection
* **pos|score** The number of targeting sgRNAs for each gene in positive selection (usually the same as num.neg)
* **pos|score** The RRA lo value of this gene in negative selection
* **pos|p-value** The raw p-value of this gene in positive selection
* **pos|fdr** The false discovery rate of this gene in positive selection
* **pos|rank**  The ranking of this gene in positive selection
* **pos|goodsgrna** The number of "good" sgRNAs, i.e., sgRNAs whose ranking is below the alpha cutoff (determined by the --gene-test-fdr-threshold option), in positive selection.
* **pos|lfc** The log fold change of this gene in positive selection

Genes are ranked by the p.neg field (by default). If you need a ranking by the p.pos, you can use the --sort-criteria option.

-----

**More Information**

**Overview of the MAGeCK algorithm**

Briefly, read counts from different samples are first median-normalized to adjust for the effect of library sizes and read count distributions. Then the variance of read counts is estimated by sharing information across features, and a negative binomial (NB) model is used to test whether sgRNA abundance differs significantly between treatments and controls. This approach is similar to those used for differential RNA-Seq analysis. We rank sgRNAs based on P-values calculated from the NB model, and use a modified robust ranking aggregation (RRA) algorithm named α-RRA to identify positively or negatively selected genes. More specifically, α-RRA assumes that if a gene has no effect on selection, then sgRNAs targeting this gene should be uniformly distributed across the ranked list of all the sgRNAs. α-RRA ranks genes by comparing the skew in rankings to the uniform null model, and prioritizes genes whose sgRNA rankings are consistently higher than expected. α-RRA calculates the statistical significance of the skew by permutation, and a detailed description of the algorithm is presented in the Materials and methods section of the `MAGeCK paper`_. Finally, MAGeCK reports positively and negatively selected pathways by applying α-RRA to the rankings of genes in a pathway.

For more information on using MAGeCK, see the `MAGeCK website here`_.

.. _`GMT file in Gene Set Enrichment Analysis (GSEA)`: http://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats#GMT:_Gene_Matrix_Transposed_file_format_.28.2A.gmt.29
.. _`GSEA MSigDB database`: http://software.broadinstitute.org/gsea/login.jsp
.. _`MAGeCK paper`: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0554-4
.. _`MAGeCK website here`: https://sourceforge.net/p/mageck/wiki/QA/#using-mageck

    ]]></help>
      <expand macro="citations" />
</tool>