Mercurial > repos > pjbriggs > weeder2
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Uploaded tool version 2.0.3.
author | pjbriggs |
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date | Wed, 26 Sep 2018 10:12:56 -0400 |
parents | f19e18ab01b1 |
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<tool id="motiffinding_weeder2" name="Weeder2" version="2.0.3"> <description>Motif discovery in sequences from coregulated genes of a single species</description> <requirements> <requirement type="package" version="2.0">weeder</requirement> </requirements> <command detect_errors="exit_code"><![CDATA[ bash $__tool_directory__/weeder2_wrapper.sh $sequence_file $species_code ${species_code.fields.path} $output_motifs_file $output_matrix_file $strands #if $chipseq.use_chipseq -chipseq -top $chipseq.top #end if #if str( $advanced_options.advanced_options_selector ) == "on" -maxm $advanced_options.n_motifs_report -b $advanced_options.n_motifs_build -sim $advanced_options.sim_threshold -em $advanced_options.em_cycles #end if ]]></command> <inputs> <param name="sequence_file" type="data" format="fasta" label="Input sequence" /> <param name="species_code" type="select" label="Species to use for background comparison"> <options from_data_table="weeder2"> </options> </param> <param name="strands" label="Use both strands of sequence" type="boolean" truevalue="" falsevalue="-ss" checked="True" help="If not checked then use -ss option" /> <conditional name="chipseq"> <param name="use_chipseq" type="boolean" label="Use the ChIP-seq heuristic" help="Speeds up the computation (-chipseq)" truevalue="yes" falsevalue="no" checked="on" /> <when value="yes"> <param name="top" type="integer" value="100" label="Number of top input sequences with oligos to scan for" help="Increase this value to improve the chance of finding motifs enriched only in a subset of your input sequences (-top)" /> </when> <when value="no"></when> </conditional> <conditional name="advanced_options"> <param name="advanced_options_selector" type="select" label="Display advanced options"> <option value="off">Hide</option> <option value="on">Display</option> </param> <when value="on"> <param name="n_motifs_report" type="integer" value="25" label="Number of discovered motifs to report" help="(-maxm)" /> <param name="n_motifs_build" type="integer" value="50" label="Number of top scoring motifs to build occurrences matrix profiles and outputs for" help="(-b)" /> <param name="sim_threshold" type="float" min="0.0" max="1.0" value="0.95" label="Similarity threshold for the redundancy filter" help="Remove motifs that are too similar, with lower values imposing a stricter filter. Must be between 0.0 and 1.0 (-sim)" /> <param name="em_cycles" type="integer" min="0" max="100" value="1" label="Number of expectation maximization (EM) cycles to perform" help="Number of cycles must be between 0 and 100 (-em)" /> </when> <when value="off"> </when> </conditional> </inputs> <outputs> <data name="output_motifs_file" format="txt" label="Weeder2 on ${on_string} (motifs)" /> <data name="output_matrix_file" format="txt" label="Weeder2 on ${on_string} (matrix)" /> </outputs> <tests> <test> <param name="sequence_file" value="weeder_in.fa" ftype="fasta" /> <param name="species_code" value="MM" /> <output name="output_motifs_file" file="weeder2_motifs.out" lines_diff="2" /> <output name="output_matrix_file" file="weeder2_matrix.out" /> </test> </tests> <help> .. class:: infomark **What it does** Weeder2 is a program for finding novel motifs (transcription factor binding sites) conserved in a set of regulatory regions of related genes. ------------- .. class:: infomark **Usage advice** Guidelines on how to use this tool can be seen in Zambelli et al. 2014 (see link below), but the following is a brief guide. Please note that **motifs** are a model or matrix that describes a set of sequences that may differ in the base composition. **Oligos** are specific sequences found within the input sequences or genomic background. **Input sequence** (in FASTA format) should be short (100-200bp) and be reasonably expected to contain an enriched motif(s). This is not generally an issue with transcription factor ChIP-seq derived sequences centred on the summit of binding regions that are expected to contain a dominant motif and possibly secondary motifs. There is **no need to mask sequence for repetitive sequence** as factors may legitimately bind repetitive sequence. **Use both strands of sequence** by default, unless there is a specific reason not to do so. **Species to use for background comparison** should match the genome used to generate the **input sequence**. The background genome motif frequencies are generated from within the promoter regions of annotated genes and are shown to be a good background for both promoter and other regulatory regions. **Use the ChIP-seq heuristic** (-chipseq) when there are a large number of input sequences (hundreds or thousands). When -chipseq is used Weeder will use only oligos from the first 100 sequences to build motifs with which it scans all of the input sequences. This speeds up the computational time without too much risk of losing important motifs. Even if not strictly necessary it's advisable to order input sequences by their significance, e.g. fold enrichment or Pvalue. For large data sets (-top) should be set to a number equating at least 10 to 20% of input sequences (as recommended by the authors). **Number of discovered motifs to report** (-maxm) limits the number of reported motifs even if there are more than -maxm. **Number of top scoring motifs to build occurrences matrix profiles and outputs for** (-b) changes the number of top scoring motifs of length 6, 8 and 10 for which the occurrence matrix is built. Increasing -b may result in a larger number of reported motifs, but with potentially more of low significance and increases the computational time. If increasing -b does not result in more motifs in your results it means that the additional motifs are filtered out by the redundancy filter or that the maximum number of reported motifs set by -maxm has been reached. **Similarity threshold for the redundancy filter** (-sim) default setting is recommended. **Number of expectation maximization (EM) cycles to perform** (-em) default is recommended. The option is included to help "clean up" the resulting motif matrices. In this version the number of EM steps can be increased, which can be useful for motifs with highly redundant stretches of sequence. ------------- .. class:: infomark **A note on the results** The resulting matrices are the result of scanning (by default both strands) for oligos of length 6, 8 and 8, allowing 1, 2 and 3 substitutions respectively. The matrices within the matrix.w2 file can be input into other tools. The recommended next step is to use **STAMP** (http://www.benoslab.pitt.edu/stamp/), which displays the motifs as logos and identifies matches with libraries of known DNA binding motifs, such as TRANSFAC or JASPAR. ------------- .. class:: infomark **Credits** This Galaxy tool has been developed by Peter Briggs and Ian Donaldson within the Bioinformatics Core Facility at the University of Manchester, and runs the Weeder2 motif discovery package: * Zambelli, F., Pesole, G. and Pavesi, G. 2014. Using Weeder, Pscan, and PscanChIP for the Discovery of Enriched Transcription Factor Binding Site Motifs in Nucleotide Sequences. Current Protocols in Bioinformatics. 47:2.11:2.11.1–2.11.31. * http://onlinelibrary.wiley.com/doi/10.1002/0471250953.bi0211s47/full This tool is compatible with Weeder 2.0: * http://159.149.160.51/modtools/downloads/weeder2.html Please kindly acknowledge both this Galaxy tool, the Weeder package and the utility scripts if you use it in your work. </help> <citations> <!-- See https://wiki.galaxyproject.org/Admin/Tools/ToolConfigSyntax#A.3Ccitations.3E_tag_set Can be either DOI or Bibtex Use http://www.bioinformatics.org/texmed/ to convert PubMed to Bibtex --> <citation type="doi">10.1002/0471250953.bi0211s47</citation> </citations> </tool>