Mercurial > repos > mora-lab > spia
changeset 3:f0759e65c834 draft
Deleted selected files
author | mora-lab |
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date | Thu, 20 May 2021 12:19:03 +0000 |
parents | 1928527cb55d |
children | 6445741c6c02 |
files | SPIA.xml |
diffstat | 1 files changed, 0 insertions(+), 168 deletions(-) [+] |
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--- a/SPIA.xml Thu May 20 12:18:48 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,168 +0,0 @@ -<tool id="SPIA" name="SPIA (Signaling Pathway Impact Analysis)" version="0.1.0" > - <description>A method based on over-representation and signaling perturbation accumulation to analyze KEGG signaling pathways.</description> - - <requirements> - <requirement type="package" version="1.20.3">r-getopt</requirement> - <requirement type="package" version="2.42.0">bioconductor-SPIA</requirement> - </requirements> - - <command detect_errors="exit_code"><![CDATA[ - Rscript '$__tool_directory__/SPIA.R' - -D '$input_data' - -O '$organism' - -R '$sigP_output' - - -P '$adv.P_value_threshold' - - -N '$adv.Number_bootstrap' - -C '$adv.method_combine_pvalue' - #if $adv.plot_perturbation=="True": - -W - -L '$SPIA_Perturbation_Plots' - #end if - - #if $adv.pathwayId !="": - -I '$adv.pathwayId' - #end if - - ]]></command> - - <inputs> - <param type="data" name="input_data" format="csv" multiple="false" label="Input data" help="A csv file including the columns ENTREZ, logFC, and adj.P.Val"/> - <param type="text" name="organism" value="hsa" label="Organism" help="A three letter character designating the organism. Default is `hsa` (human). See a full list at https://www.genome.jp/kegg/catalog/org_list.html" /> - - <section name="adv" title="Advanced Options" expanded="false"> - <param type="float" name="P_value_threshold" label="P value threshold to select DEgenes" value="0.05" min="0.00" max="1.00" help="Set a threshold value to define differentially expressed genes"/> - <param type="integer" name="Number_bootstrap" value="2000" min="100" label="Bootstrap iterations" help="Number of bootstrap iterations used to compute the P PERT value. Should be larger than 100. A recommended value is 2000." /> - <param type="select" name="method_combine_pvalue" label="Method to combine P values" help="Method used to combine the two types of p-values. If set to 'fisher' it will use Fisher's method. If set to 'norminv' it will use the normal inversion method."> - <option value="fisher" selected="True">fisher</option> - <option value="norminv">norminv</option> - </param> - <param type="boolean" name="plot_perturbation" truevalue="True" falsevalue="False" checked="False" label="Plot perturbation" help="If set to Yes, plot the gene perturbation accumulation vs log2 fold change for every gene on each pathway. Default is No." /> - <param type="text" name="pathwayId" value="" label="Pathway IDs -- default as NULL and analysis all pathway. " help="Special one or more pathway to analysis, input pathway ID at here. For example: 03018, 03320."/> - </section> - - </inputs> - - <outputs> - <data name="sigP_output" format="csv" label="SPIA_enrich_kegg" /> - <data format="pdf" name="SPIA_Perturbation_Plots" label="SPIA_Perturbation_Plots"> - <filter>adv['plot_perturbation'] == True</filter> - </data> - </outputs> - - <tests> - <test> - <param name="input_data" value="SPIA_input.csv" ftype="csv" /> - <output name="sigP_output" file="x.csv" ftype="csv" /> - </test> - </tests> - - <help><![CDATA[ - - .. class:: infomark - - **What it does** - - SPIA (Signaling pathway impact analysis) combines the evidence obtained from the - classical enrichment analysis with a novel type of evidence, which measures the actual - perturbation on a given pathway under a given condition. - - A bootstap procedure is used to assess the significance of the observed total pathway perturbation. - - Then we can calculate a global pathway significance P-value, which combines the enrichment and perturbation P-values. - - SPIA tool analyzes KEGG signaling pathways. - -------- - -========= -**Input** -========= - -Basic options --------------- - -**Input data** - -The input data is a csv file, which includes the columns `ENTREZ`, `logFC` and `adj.P.Val`. -This file contains all genes of your dataset. - - ====== ========== ======= ========== ========= ==== ======== - logFC AveExpr t P.Value adj.P.Val B ENTREZ - ====== ========== ======= ========== ========= ==== ======== - 5.96 6.23 23.9 1.79e-17 9.78e-13 25.4 3491 - 5.14 7.49 17.4 1.56e-14 2.84e-10 21.0 2353 - 4.15 7.04 16.5 5.15e-14 7.04e-10 20.1 1958 - 2.43 9.59 14.1 1.29e-12 1.41e- 8 17.7 1843 - 1.53 8.22 11.0 1.69e-10 1.15e- 6 13.6 3725 - 1.43 5.33 10.5 4.27e-10 2.42e- 6 12.8 23645 - ====== ========== ======= ========== ========= ==== ======== - -**Organism** - -A three letter word designating the organism of your data. Default is `hsa` (Human). See a full list of options at https://www.genome.jp/kegg/catalog/org_list.html. - ------- - -Advanced Options ------------------ - -**P value threshold to select DEgenes** - -Set a threshold value to define differentially expressed genes. Default is 0.05. - -**Bootstrap iterations** - -Number of bootstrap iterations used to compute the `pPERT` value. Should be larger than 100. A recommended value is 2000. - -**Method to combine P values** - -Method used to combine the two types of p-values. If set to 'fisher' it will use Fisher's method. If set to 'norminv' it will use the normal inversion method. - -**Plot perturbation** - -If set to `Yes`, plots the gene perturbation accumulation vs log2 fold change for every gene on each pathway. Default is `No`. - -**Pathway IDs -- default as NULL and analysis all pathway.** - -if you want special one or more pathway to analysis, Input pathway id at here. for example: `03018, 03320`. - ------- - -========== -**Output** -========== - - **CSV file** - - This file contains the ranked pathways and various statistics: - - **Name** is the pathway name; - - **ID** is the pathway ID; - - **pSize** is the number of genes on the pathway; - - **NDE** is the number of DE genes per pathway; - - **tA** is the observed total perturbation accumulation in the pathway; - - **pNDE** is the probability to observe at least NDE genes on the pathway using a hypergeometric model; - - **pPERT** is the probability to observe a total accumulation more extreme than tA only by chance; - - **pG** is the p-value obtained by combining pNDE and pPERT; - - **pGFdr** and **pGFWER** are the False Discovery Rate and Bonferroni adjusted global p-values; - - **Status** gives the direction in which the pathway is perturbed (activated or inhibited). - - **KEGGLINK** gives a web link to the KEGG website that displays the pathway image with the differentially expressed genes highlighted in red. - - **PDF file** - - If the plot argument is set to `Yes`, it will output the plots for the gene perturbation accumulation vs log2 fold change for every gene on each pathway. - ------- - -Please cite SPIA_ appropriately if you use them. - -.. _SPIA: https://pubmed.ncbi.nlm.nih.gov/18990722/ - - ]]></help> - - <citations> - <citation type="doi">10.1093/bioinformatics/btn577</citation> - </citations> - -</tool>