Explore Workflows
View already parsed workflows here or click here to add your own
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conflict-wf.cwl#collision
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Path: cwltool/schemas/v1.0/v1.0/conflict-wf.cwl Branch/Commit ID: 2ae8117360a3cd4909d9d3f2b35c30bfffb25d0a Packed ID: collision |
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bam to trimmed fastqs and HISAT alignments
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Path: definitions/subworkflows/bam_to_trimmed_fastq_and_hisat_alignments.cwl Branch/Commit ID: 6f9f8a2057c6a9f221a44559f671e87a75c70075 |
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scatter-valuefrom-wf4.cwl#main
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Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf4.cwl Branch/Commit ID: d7cd45f7072960d264962ecc5a04d7c219f65c06 Packed ID: main |
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811.cwl
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Path: tests/wf/811.cwl Branch/Commit ID: dbc4c4c2ad30ed31367b4fbcc3bb4084fdcabaa2 |
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MAnorm PE - quantitative comparison of ChIP-Seq paired-end data
What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General **Experiment short name/Alias** * short name for you experiment to identify among the others **ChIP-Seq PE sample 1** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 **ChIP-Seq PE sample 2** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 2 **Genome** * Reference genome to be used for gene assigning ### Advanced **Reads shift size for sample 1** * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **Reads shift size for sample 2** * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **M-value (log2-ratio) cutoff** * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 **P-value cutoff** * P-value cutoff to define biased peaks. Default: 0.01 **Window size** * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000 |
Path: workflows/manorm-pe.cwl Branch/Commit ID: 7ae3b75bbe614e59cdeaba06047234a6c40c0fe9 |
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scatter-wf3_v1_1.cwl#main
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Path: testdata/scatter-wf3_v1_1.cwl Branch/Commit ID: 7af75226f084349e401b1114f25bdcdee060e127 Packed ID: main |
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workflow_same_level.cwl#second_pipeline
Simulation of 2 workflows |
Path: workflow_in_workflow/workflow_same_level.cwl Branch/Commit ID: 2f678aa688683e20169abaaec9166b4a32403523 Packed ID: second_pipeline |
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Seed Search Compartments
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Path: protein_alignment/wf_seed.cwl Branch/Commit ID: 01a5c0a8834846ce04fed190eec7d1cc39a3df48 |
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FASTQ Download
FASTQ Download Assists in downloading problematic single-cell sequencing data from Sequence Read Archive (SRA) |
Path: workflows/fastq-download.cwl Branch/Commit ID: 69643d8c15f5357a320aa7e2f6adb2e71302fd20 |
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SoupX (workflow) - an R package for the estimation and removal of cell free mRNA contamination
Wrapped in a workflow SoupX tool for easy access to Cell Ranger pipeline compressed outputs. |
Path: tools/soupx-subworkflow.cwl Branch/Commit ID: 7826a52718f052b53cc3872dcb3619a61babb44b |
