Explore Workflows
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count-lines7-wf_v1_0.cwl
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Path: testdata/count-lines7-wf_v1_0.cwl Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7 |
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record-output-wf_v1_2.cwl
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Path: testdata/record-output-wf_v1_2.cwl Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7 |
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record-output-wf_v1_0.cwl
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Path: testdata/record-output-wf_v1_0.cwl Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7 |
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scatter GATK HaplotypeCaller over intervals
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Path: definitions/subworkflows/gatk_haplotypecaller_iterator.cwl Branch/Commit ID: 39ac49f5d080bbb6bfa97246f46a5b621254f622 |
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md5sum.cwl
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Path: testdata/md5sum.cwl Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7 |
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Interval overlapping alignments counts
Interval overlapping alignments counts ====================================== Reports the count of alignments from multiple samples that overlap specific intervals. |
Path: workflows/bedtools-multicov.cwl Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895 |
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miRNA-Seq miRDeep2 pipeline
A CWL workflow for discovering known or novel miRNAs from deep sequencing data using the miRDeep2 tool. The ExoCarta exosome database is also used for identifying exosome-related miRNAs, and TargetScan's organism-specific databases are used for identifying miRNA gene targets. ## __Outputs__ #### Primary Output files: - mirs_known.tsv, detected known mature miRNAs, \"Known miRNAs\" tab - mirs_novel.tsv, detected novel mature miRNAs, \"Novel miRNAs\" tab #### Secondary Output files: - mirs_known_exocarta_deepmirs.tsv, list of detected miRNA also in ExoCarta's exosome database, \"Detected Exosome miRNAs\" tab - mirs_known_gene_targets.tsv, pre-computed gene targets of known mature mirs, downloadable - known_mirs_mature.fa, known mature mir sequences, downloadable - known_mirs_precursor.fa, known precursor mir sequences, downloadable - novel_mirs_mature.fa, novel mature mir sequences, downloadable - novel_mirs_precursor.fa, novel precursor mir sequences, downloadable #### Reports: - overview.md (input list, alignment & mir metrics), \"Overview\" tab - mirdeep2_result.html, summary of mirdeep2 results, \"miRDeep2 Results\" tab ## __Inputs__ #### General Info - Sample short name/Alias: unique name for sample - Experimental condition: condition, variable, etc name (e.g. \"control\" or \"20C 60min\") - Cells: name of cells used for the sample - Catalog No.: vender catalog number if available - Bowtie2 index: Bowtie2 index directory of the reference genome. - Reference Genome FASTA: Reference genome FASTA file to be used for alignment. - Genome short name: Name used for setting organism name, genus, species, and tax ID. - Input FASTQ file: FASTQ file from a single-end miRNA sequencing run. #### Advanced - Adapter: Adapter sequence to be trimmed from miRNA sequence reads. (Default: TCGTAT) - Threads: Number of threads to use for steps that support multithreading (Default: 4). ## Hints & Tips: #### For the identification of novel miRNA candidates, the following may be used as a filtering guideline: 1. miRDeep score > 4 (some authors use 1) 2. not present a match with rfam 3. should present a significant RNAfold (\"yes\") 4. a number of mature reads > 10 5. if applicable, novel mir must be expressed in multiple samples #### For filtering mirbase by organism. | genome | organism | division | name | tree | NCBI-taxid | | ---- | --- | --- | ----------- | ----------- | ----------- | | hg19 | hsa | HSA | Homo sapiens | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Primates;Hominidae | 9606 | | hg38 | hsa | HSA | Homo sapiens | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Primates;Hominidae | 9606 | | mm10 | mmu | MMU | Mus musculus | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Rodentia | 10090 | | rn7 | rno | RNO | Rattus norvegicus | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Rodentia | 10116 | | dm3 | dme | DME | Drosophila melanogaster | Metazoa;Bilateria;Ecdysozoa;Arthropoda;Hexapoda | 7227 | ## __Data Analysis Steps__ 1. The miRDeep2 Mapper module processes Illumina FASTQ output and maps it to the reference genome. 2. The miRDeep2 miRDeep2 module identifies known and novel (mature and precursor) miRNAs. 3. The ExoCarta database of miRNA found in exosomes is then used to find overlap between mirs_known.tsv and exosome associated miRNAs. 4. Finally, TargetScan organism-specific miRNA gene target database is used to find overlap between mirs_known.tsv and gene targets. ## __References__ 1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245920 2. https://github.com/rajewsky-lab/mirdeep2 3. https://biocontainers.pro/tools/mirdeep2 4. https://www.mirbase.org/ 5. http://exocarta.org/index.html 6. https://www.targetscan.org/vert_80/ |
Path: workflows/mirna-mirdeep2-se.cwl Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895 |
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DESeq2 Multi-factor Analysis
DESeq2 Multi-factor Analysis Runs DeSeq2 multi-factor analysis with manual control over major parameters |
Path: workflows/deseq-multi-factor.cwl Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895 |
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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. |
Path: workflows/bwa-index.cwl Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895 |
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taxonomy_check_16S
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Path: task_types/tt_taxonomy_check_16S.cwl Branch/Commit ID: a402541b8530f30eab726c160da90a23036847a1 |
