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author | iuc |
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date | Thu, 16 Jan 2014 16:48:26 -0500 |
parents | d202e3d663bb |
children | da0a1fcf7fe0 |
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<tool id="macs2_bdgcmp" name="Deduct noise" version="2.0.10.0"> <description>by comparing two signal tracks in bedGraph (bdgcmp)</description> <expand macro="requirements" /> <expand macro="version_command" /> <macros> <import>macs2_macros.xml</import> </macros> <command> macs2 bdgcmp -t $input_treatment_file -c $input_control_file -m $bdgcmp_options.bdgcmp_options_selector #if $bdgcmp_options.bdgcmp_options_selector in ['FE', 'logFR', 'logLR']: -p $pseudocount #end if --ofile $ofile </command> <inputs> <!--experiment name and option of selecting paired or single end will always be present--> <param name="experiment_name" type="text" value="MACS2 in Galaxy" size="50" label="Experiment Name"/> <param name="input_treatment_file" type="data" format="bedgraph" label="Treatment bedGraph file" /> <param name="input_control_file" type="data" format="bedgraph" label="Control bedGraph file" /> <conditional name="bdgcmp_options"> <param name="bdgcmp_options_selector" type="select" label="Method to use while calculating a score in any bin by comparing treatment value and control value"> <option value="ppois">Poisson Pvalue (-log10 (pvalue) form) using control as lambda and treatment as observation</option> <option value="qpois">q-value through a BH process for poisson pvalues</option> <option value="subtract">subtraction from treatment</option> <option value="logFE">log10 fold enrichment</option> <option value="FE">linear scale fold enrichment</option> <option value="logLR">log10 likelihood between ChIP-enriched model and open chromatin model</option> <option value="slogLR">symmetric log10 likelihood between two ChIP-enrichment models and open chromatin model</option> </param> <when value="FE"> <param name="pseudocount" type="float" label="Set pseudocount" value="0.0" help="The count will be applied after normalization of sequencing depth. DEFAULT: 0.0, no pseudocount is applied."/> </when> <when value="logLR"> <param name="pseudocount" type="float" label="Set pseudocount" value="0.0" help="The count will be applied after normalization of sequencing depth. DEFAULT: 0.0, no pseudocount is applied."/> </when> <when value="logFE"> <param name="pseudocount" type="float" label="Set pseudocount" value="0.0" help="The count will be applied after normalization of sequencing depth. DEFAULT: 0.0, no pseudocount is applied."/> </when> </conditional> </inputs> <outputs> <data name="ofile" format="bedgraph" label="${tool.name} on ${on_string}" /> </outputs> <tests> <!--none yet for macs2--> </tests> <help> **What it does** With the improvement of sequencing techniques, chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) is getting popular to study genome-wide protein-DNA interactions. To address the lack of powerful ChIP-Seq analysis method, we present a novel algorithm, named Model-based Analysis of ChIP-Seq (MACS), for identifying transcript factor binding sites. MACS captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. MACS can be easily used for ChIP-Seq data alone, or with control sample with the increase of specificity. View the original MACS2 documentation: https://github.com/taoliu/MACS/blob/master/README ------ **Usage** **Peak Calling**: Main MACS2 Function to Call peaks from alignment results. **Compare .bdg files**: Deduct noise by comparing two signal tracks in bedGraph. ------ **Citation** For the underlying tool, please cite Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. Integration of MACS2 with Galaxy performed by Ziru Zhou ( ziruzhou@gmail.com ). Please send your comments/questions to modENCODE DCC at help@modencode.org. </help> </tool>