Explore Workflows
View already parsed workflows here or click here to add your own
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Seed Protein Alignments I
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https://github.com/ncbi/pgap.git
Path: protein_alignment/wf_seed_1.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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Seed Protein Alignments I
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https://github.com/ncbi/pgap.git
Path: protein_alignment/wf_seed_1.cwl Branch/Commit ID: 42712bca4c3307d87b6b55f525a4c97cb6f7e288 |
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Seed Search Compartments
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https://github.com/ncbi/pgap.git
Path: protein_alignment/wf_seed.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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trnascan_wnode and gpx_qdump combined
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https://github.com/ncbi/pgap.git
Path: bacterial_trna/wf_scan_and_dump.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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Run genomic CMsearch (5S rRNA)
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https://github.com/ncbi/pgap.git
Path: bacterial_noncoding/wf_gcmsearch.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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adapter for sequence_align_and_tag
Some workflow engines won't stage files in our nested structure, so parse it out here |
https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/sequence_align_and_tag_adapter.cwl Branch/Commit ID: 54846feabbf008c1946db2a86d87252e0edd95b0 |
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Run genomic CMsearch (5S rRNA)
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https://github.com/ncbi/pgap.git
Path: bacterial_noncoding/wf_gcmsearch.cwl Branch/Commit ID: 4f4448f71645275db5b84eb551990dfe3bf37cbb |
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MAnorm SE - quantitative comparison of ChIP-Seq single-read 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 SE sample 1** * previously analyzed ChIP-Seq single-read experiment to be used as Sample 1 **ChIP-Seq SE sample 2** * previously analyzed ChIP-Seq single-read 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 |
https://github.com/datirium/workflows.git
Path: workflows/manorm-se.cwl Branch/Commit ID: d1bef74924efcb8bfaa00987b3f148d5a192b7a9 |
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tt_hmmsearch_wnode.cwl
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https://github.com/ncbi/pgap.git
Path: task_types/tt_hmmsearch_wnode.cwl Branch/Commit ID: 2229f26ec424f9ebeb3db7fec3bd3f84a38c7485 |
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HS Metrics workflow
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/hs_metrics.cwl Branch/Commit ID: 54846feabbf008c1946db2a86d87252e0edd95b0 |
