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Graph Name Retrieved From View
workflow graph Create Genomic Collection for Bacterial Pipeline, ASN.1 input

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

Path: genomic_source/wf_genomic_source_asn.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph spurious_annot pass2

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

Path: spurious_annot/wf_spurious_annot_pass2.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph checkm

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

Path: checkm/wf_checkm.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph Bacterial Annotation, pass 3, structural annotation, functional annotation: ab initio GeneMark, by WP, by HMM (second pass)

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

Path: bacterial_annot/wf_bacterial_annot_pass3.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph Get Proteins

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

Path: wf_bacterial_prot_src.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph Bacterial Annotation, pass 1, genemark training, by HMMs (first pass)

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

Path: bacterial_annot/wf_bacterial_annot_pass1.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph Run tRNAScan

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

Path: bacterial_trna/wf_trnascan.cwl

Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc
workflow graph 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: d76110e0bfc40c874f82e37cef6451d74df4f908
workflow graph Deprecated. AltAnalyze Build Reference Indices

Deprecated. AltAnalyze Build Reference Indices

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

Path: workflows/altanalyze-prepare-genome.cwl

Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908
workflow graph BWA index pipeline

This workflow indexes the input reference FASTA with bwa, and generates faidx and dict file using samtools. This index sample can then be used as input into the germline variant calling workflow, or others that may include this workflow as an upstream source. ### __Inputs__ - FASTA file of the reference genome that will be indexed. ### __Outputs__ - Directory containing the original FASTA, faidx, dict, and bwa index files. - stdout log file (output in Overview tab as well) - stderr log file ### __Data Analysis Steps__ 1. cwl calls dockercontainer robertplayer/scidap-gatk4 to index reference FASTA with bwa, and generates faidx and dict files using samtools ### __References__ - Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754–1760.

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

Path: workflows/bwa-index.cwl

Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908