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Graph Name Retrieved From View
workflow graph THOR - differential peak calling of ChIP-seq signals with replicates

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86

workflow graph prefactor_target.cwl

https://git.astron.nl/eosc/prefactor3-cwl.git

Path: workflows/prefactor_target.cwl

Branch/Commit ID: 5f6da86a561d1b1c5b7ef56dc8bbbb1f1d7e9cbe

workflow graph RNA-Seq pipeline single-read

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-read** 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-read RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 3. 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/rnaseq-se.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

workflow graph format_rrnas_from_seq_entry

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

Path: task_types/tt_format_rrnas_from_seq_entry.cwl

Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc

workflow graph samtools_sort

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/subworkflows/samtools_sort.cwl

Branch/Commit ID: f248ac3ccbf6840af721251c7e9451abd9b2c09f

workflow graph align_merge_sas

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

Path: task_types/tt_align_merge_sas.cwl

Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc

workflow graph taxonomy_check_16S

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

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: 2353ee2550529ca5b0705c94b32022a21713db18

workflow graph Functional analyis of sequences that match the 16S SSU

https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git

Path: workflows/16S_taxonomic_analysis.cwl

Branch/Commit ID: ecf044f3a5a7589cb2238487a19f22863c2bcdb1

workflow graph DESeq2 (LRT) - differential gene expression analysis using likelihood ratio test

Runs DESeq2 using LRT (Likelihood Ratio Test) ============================================= The LRT examines two models for the counts, a full model with a certain number of terms and a reduced model, in which some of the terms of the full model are removed. The test determines if the increased likelihood of the data using the extra terms in the full model is more than expected if those extra terms are truly zero. The LRT is therefore useful for testing multiple terms at once, for example testing 3 or more levels of a factor at once, or all interactions between two variables. The LRT for count data is conceptually similar to an analysis of variance (ANOVA) calculation in linear regression, except that in the case of the Negative Binomial GLM, we use an analysis of deviance (ANODEV), where the deviance captures the difference in likelihood between a full and a reduced model. When one performs a likelihood ratio test, the p values and the test statistic (the stat column) are values for the test that removes all of the variables which are present in the full design and not in the reduced design. This tests the null hypothesis that all the coefficients from these variables and levels of these factors are equal to zero. The likelihood ratio test p values therefore represent a test of all the variables and all the levels of factors which are among these variables. However, the results table only has space for one column of log fold change, so a single variable and a single comparison is shown (among the potentially multiple log fold changes which were tested in the likelihood ratio test). This indicates that the p value is for the likelihood ratio test of all the variables and all the levels, while the log fold change is a single comparison from among those variables and levels. **Technical notes** 1. At least two biological replicates are required for every compared category 2. Metadata file describes relations between compared experiments, for example ``` ,time,condition DH1,day5,WT DH2,day5,KO DH3,day7,WT DH4,day7,KO DH5,day7,KO ``` where `time, condition, day5, day7, WT, KO` should be a single words (without spaces) and `DH1, DH2, DH3, DH4, DH5` correspond to the experiment aliases set in **RNA-Seq experiments** input. 3. Design and reduced formulas should start with **~** and include categories or, optionally, their interactions from the metadata file header. See details in DESeq2 manual [here](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#interactions) and [here](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#likelihood-ratio-test) 4. Contrast should be set based on your metadata file header and available categories in a form of `Factor Numerator Denominator`, where `Factor` - column name from metadata file, `Numerator` - category from metadata file to be used as numerator in fold change calculation, `Denominator` - category from metadata file to be used as denominator in fold change calculation. For example `condition WT KO`.

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

Path: workflows/deseq-lrt.cwl

Branch/Commit ID: 9e3c3e65c19873cd1ed3cf7cc3b94ebc75ae0cc5

workflow graph align_merge_sas

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

Path: task_types/tt_align_merge_sas.cwl

Branch/Commit ID: 72804b6506c9f54ec75627f82aafe6a28d7a49fa