Explore Workflows

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

Path: v1.0/v1.0/count-lines11-extra-step-wf-noET.cwl

Branch/Commit ID: 4d06b9efd26c5813c13684ebcc95547bb75ddfcc

https://github.com/PMCC-BioinformaticsCore/janis-pipelines.git

Path: janis_pipelines/wgs_somatic/cwl/tools/AddBamStatsSomatic_v0_1_0.cwl

Branch/Commit ID: c1aeec7b68acdd1eab3f1d1bd75d768e31abd6d2

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

Path: definitions/subworkflows/pindel_cat.cwl

Branch/Commit ID: 5c4125344b1b9125ad04d7e768ecc99901570a7a

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

Path: definitions/subworkflows/bam_to_trimmed_fastq.cwl

Branch/Commit ID: 74647cc0f1abac4ee22950cfa89c44cf2ca3cffd

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

Path: task_types/tt_kmer_compare_wnode.cwl

Branch/Commit ID: a539d600357a48a558daf43fc41a89aae79f9e86

Devel version of AltAnalyze Iterative Clustering and Guide-gene Selection =========================================================================

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

Path: workflows/altanalyze-icgs.cwl

Branch/Commit ID: 64f7fe4438898218fd83133efa25251078f5b27e

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

Path: definitions/subworkflows/qc_exome_no_verify_bam.cwl

Branch/Commit ID: 74647cc0f1abac4ee22950cfa89c44cf2ca3cffd

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: 799575ce58746813f066a665adeacdda252d8cab

https://github.com/NCI-GDC/gdc-mirnaseq-cwl.git

Path: workflows/mirnaseq_automation/mirna_profiling.cwl

Branch/Commit ID: 963f6d502da2c4f152c1654e94008ccf8f6d0db3

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

Path: definitions/subworkflows/align_sort_markdup.cwl

Branch/Commit ID: 74647cc0f1abac4ee22950cfa89c44cf2ca3cffd