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Graph Name Retrieved From View
workflow graph 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

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

Path: workflows/manorm-pe.cwl

Branch/Commit ID: 480e99a4bb3046e0565113d9dca294e0895d3b0c
workflow graph bact_get_kmer_reference

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 17bae57a1f00f5c6db8f3a82d86262f12b8153cf
workflow graph cluster_blastp_wnode and gpx_qdump combined

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: 5e92165ac2c11608ab2db42fe2d66eabe72dbb40
workflow graph Creates FASTA file from BED coordinates

This workflow creates FASTA file from BED coordinates

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

Path: workflows/File-formats/fasta-from-bed.cwl

Branch/Commit ID: f9447c1ac522e17531097c93a169a1a31453e874
workflow graph Detect DoCM variants

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

Path: definitions/subworkflows/docm_germline.cwl

Branch/Commit ID: ec5355f335852e51c6938809c16ea1d230a3f983
workflow graph Nanopore assembly workflow

Workflow for sequencing with ONT nanopore, from basecalled reads to (meta)assembly and binning Steps: - Read filtering - Kraken2 (taxonomic classification of FASTQ reads) - Flye (de novo assembly) - Medaka (assembly polishing) - metaQUAST (assembly quality reports) When Illumina reads are provided: - Assembly polishing with Pilon Binnning: - Metabat2 - CheckM - BUSCO - GTDB-Tk

https://git.wur.nl/unlock/cwl.git

Path: cwl/workflows/workflow_nanopore_assembly.cwl

Branch/Commit ID: cd0c19d51068c5407cd70b718a561d4662819d87
workflow graph facets-suite-workflow.cwl

Workflow for running the facets suite workflow on a single tumor normal pair Includes handling of errors in case execution fails for the sample pair

https://github.com/mskcc/pluto-cwl.git

Path: cwl/facets-suite-workflow.cwl

Branch/Commit ID: ab0192b19d01046d5db2fc5233678a97b47210e6
workflow graph Raw sequence data to BQSR

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

Path: definitions/subworkflows/sequence_to_bqsr.cwl

Branch/Commit ID: 6949082038c1ad36d6e9848b97a2537aef2d3805
workflow graph Single-cell Differential Expression

Single-cell Differential Expression =================================== Runs differential expression analysis for a subset of cells between two selected conditions.

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

Path: workflows/sc_diff_expr.cwl

Branch/Commit ID: 480e99a4bb3046e0565113d9dca294e0895d3b0c
workflow graph ani_top_n

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

Path: task_types/tt_ani_top_n.cwl

Branch/Commit ID: 5e92165ac2c11608ab2db42fe2d66eabe72dbb40