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Graph | Name | Retrieved From | View |
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Motif Finding with HOMER with random background regions
Motif Finding with HOMER with random 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. Here is how we generate background for Motifs Analysis ------------------------------------- 1. Take input file with regions in a form of “chr\" “start\" “end\" 2. Sort and remove duplicates from this regions file 3. Extend each region in 20Kb into both directions 4. Merge all overlapped extended regions 5. Subtract not extended regions from the extended ones 6. Randomly distribute not extended regions within the regions that we got as a result of the previous step 7. Get fasta file from these randomly distributed regions (from the previous step). Use it as background For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis.cwl Branch/Commit ID: b1a5dabeeeb9079b30b2871edd9c9034a1e00c1c |
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scatter-wf2.cwl
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https://github.com/common-workflow-language/cwl-v1.1.git
Path: tests/scatter-wf2.cwl Branch/Commit ID: 0e37d46e793e72b7c16b5ec03e22cb3ce1f55ba3 |
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Find reads with predicted coding sequences above 60 AA in length
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https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git
Path: workflows/orf_prediction.cwl Branch/Commit ID: 7bb76f33bf40b5cd2604001cac46f967a209c47f |
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Trim Galore RNA-Seq pipeline single-read strand specific
Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **single-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ file 2. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 4. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file |
https://github.com/datirium/workflows.git
Path: workflows/trim-rnaseq-se-dutp.cwl Branch/Commit ID: 60854b5d299df91e135e05d02f4be61f6a310fbc |
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taxonomy_check_16S
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https://github.com/ncbi/pgap.git
Path: task_types/tt_taxonomy_check_16S.cwl Branch/Commit ID: 92118627c800e4addb7e29b9dabcca073a5bae71 |
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umi duplex alignment workflow
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/duplex_alignment.cwl Branch/Commit ID: 25eab0390f6866ce491b44c89d9e0435d228ab6f |
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tt_hmmsearch_wnode.cwl
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https://github.com/ncbi/pgap.git
Path: task_types/tt_hmmsearch_wnode.cwl Branch/Commit ID: f1eb0f4eaaf1661044f28d859f7e8d4302525ead |
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dynresreq-workflow.cwl
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https://github.com/common-workflow-language/cwl-v1.1.git
Path: tests/dynresreq-workflow.cwl Branch/Commit ID: 0e37d46e793e72b7c16b5ec03e22cb3ce1f55ba3 |
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bact_get_kmer_reference
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https://github.com/ncbi/pgap.git
Path: task_types/tt_bact_get_kmer_reference.cwl Branch/Commit ID: 72804b6506c9f54ec75627f82aafe6a28d7a49fa |
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blastp_wnode_struct
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https://github.com/ncbi/pgap.git
Path: task_types/tt_blastp_wnode_struct.cwl Branch/Commit ID: 92118627c800e4addb7e29b9dabcca073a5bae71 |