Explore Workflows

https://github.com/KBNLresearch/ochre.git

Path: ochre/cwl/ocrevaluation-performance-wf-pack.cwl

Branch/Commit ID: a62bf3b31df83784c017d30a83ed8e01d454bf1c

Packed ID: main

https://github.com/mr-c/4dn-dcic-pipelines-cwl.git

Path: cwl_awsem_v1/hi-c-processing-parta-juicer.cwl

Branch/Commit ID: 895a101d06c26f8c7f8a63545b2b74921b5f7526

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

Path: definitions/subworkflows/umi_alignment.cwl

Branch/Commit ID: 449bc7e45bb02316d040f73838ef18359e770268

This workflow download SRA samples and aligng them to a transcriptome fasta file

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/Annotation/transcriptome-read-assignment.cwl

Branch/Commit ID: de6380d83f9209e95559e66cf64ded3bf0e410ea

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

Path: task_types/tt_kmer_top_n_extract.cwl

Branch/Commit ID: 041a234a935c7af7d3db95353ef80c61c88fc010

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

Path: definitions/subworkflows/align_sort_markdup.cwl

Branch/Commit ID: 449bc7e45bb02316d040f73838ef18359e770268

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

Path: cwltool/schemas/v1.0/v1.0/step-valuefrom2-wf.cwl

Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7

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

Path: tools/SSU-from-tablehits.cwl

Branch/Commit ID: 5e8217435bcdd597b2ad236f3e847d13d4c21824

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: 29bf638904709cfbf10908adcd51ba4886ace94a

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

Path: task_types/tt_kmer_build_tree.cwl

Branch/Commit ID: 33414c888997d558bdcb558ca33c3a728a3e6143