Explore Workflows

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/duplex_alignment.cwl

Branch/Commit ID: 2e0562a5c3cd7aac24af4c622a5ae68a7fb23a71

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/scatter2.cwl

Branch/Commit ID: 445f6b3a214f0c48317b25f7af278ae919ce5403

https://github.com/ncbi/pgap.git

Path: task_types/tt_kmer_cache_retrieve.cwl

Branch/Commit ID: 75ea689c0a8c9902b4598b453455857cb08e885a

https://github.com/nal-i5k/organism_onboarding.git

Path: flow_apollo2_data_processing/processing/workflow.cwl

Branch/Commit ID: 39b1d1a39a2ccdadd52db15b41422ecccc66e605

https://github.com/common-workflow-language/common-workflow-language.git

Path: v1.0/v1.0/scatter-wf4.cwl

Branch/Commit ID: e67f19d8a713759d761ecad050966d1eb043b85c

Packed ID: main

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

https://github.com/datirium/workflows.git

Path: workflows/manorm-pe.cwl

Branch/Commit ID: 9850a859de1f42d3d252c50e15701928856fe774

https://github.com/proteinswebteam/ebi-metagenomics-cwl.git

Path: workflows/cmsearch-multimodel.cwl

Branch/Commit ID: 25129f55226dee595ef941edc24d3c44414e0523

https://github.com/ncbi/pgap.git

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: 7cee09fb3e33c851e4e1dfc965c558b82290a785

https://github.com/manabuishii/cwl-samples.git

Path: grep-and-count.cwl

Branch/Commit ID: 752ef34cfa64ba020ef2d70924fb1e8fea889612

This workflow returns the reproducible number of split peaks given a single bam file and its size-matched input pair. This workflow splits the bam file first, but does not do anything to the input.

https://github.com/YeoLab/merge_peaks.git

Path: cwl/wf_split_self_and_idr.cwl

Branch/Commit ID: aedc0a14d4ba109ee65678a3201a52c5bb6ad473