Explore Workflows
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Build Bismark indices
Copy fasta_file file to the folder and run run bismark_genome_preparation script to prepare indices for Bismark Methylation Analysis. Bowtie2 aligner is used by default. The name of the output indices folder is equal to the genome input. |
![]() Path: workflows/bismark-index.cwl Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908 |
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advanced-header.cwl
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![]() Path: metadata/advanced-header.cwl Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908 |
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rnaseq-pe-dutp.cwl
Runs RNA-Seq BioWardrobe basic analysis with strand specific pair-end data file. |
![]() Path: workflows/rnaseq-pe-dutp.cwl Branch/Commit ID: 896422c9ff1995024cb77675edcd4d973ae11f7a |
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Motif Finding with HOMER with custom background regions
Motif Finding with HOMER with custom background regions --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/) |
![]() Path: workflows/homer-motif-analysis-bg.cwl Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908 |
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group-isoforms-batch.cwl
Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored. |
![]() Path: tools/group-isoforms-batch.cwl Branch/Commit ID: 896422c9ff1995024cb77675edcd4d973ae11f7a |
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kmer_build_tree
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![]() Path: task_types/tt_kmer_build_tree.cwl Branch/Commit ID: 2d851682ba1bf2aaaacb3677253b55ceb59c8568 |
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bam_readcount workflow
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![]() Path: definitions/subworkflows/bam_readcount.cwl Branch/Commit ID: 5fda2d9eb52a363bd51011b3851c2afb86318c0c |
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Salmon quantification, FASTQ -> H5AD count matrix
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![]() Path: steps/salmon-quantification.cwl Branch/Commit ID: a9d8c3c491945e8ebd6bb777c6bdd1a7e5671556 |
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Cell Ranger Count (RNA)
Cell Ranger Count (RNA) Quantifies single-cell gene expression of the sequencing data from a single 10x Genomics library. The results of this workflow are primarily used in either “Single-Cell RNA-Seq Filtering Analysis” or “Cell Ranger Aggregate (RNA, RNA+VDJ)” pipelines. |
![]() Path: workflows/single-cell-preprocess-cellranger.cwl Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908 |
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blastp_wnode_naming
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![]() Path: task_types/tt_blastp_wnode_naming.cwl Branch/Commit ID: 5b498b4c4f17bb8f17e6886aa4c5661d7aba34fc |