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SEEK ID: https://workflowhub.eu/projects/269
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Team created: 7th Sep 2024
Related items
Teams: Intergalactic Workflow Commission (IWC), Vertebrate Genomes Pipelines in Galaxy, nf-core, iwc
Organizations: Bots, European Galaxy Team
This workflow takes as input SR BAM from ChIP-seq. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.
This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. In parallel it processes the Gene Expresion fastqs with STARsolo, filter cells with DropletUtils and reformat all outputs to be easily used by the function 'Read10X' from Seurat.
Type: Galaxy
Creators: Lucille Delisle, Mehmet Tekman, Hans-Rudolf Hotz, Daniel Blankenberg, Wendi Bacon
Submitter: WorkflowHub Bot
A workflow for the analysis of pox virus genomes sequenced as half-genomes (for ITR resolution) in a tiled-amplicon approach
Automated inference of stable isotope incorporation rates in proteins for functional metaproteomics
Generate Nx and Size plot for multiple assemblies
Inputs
Collection of fasta files. The name of each item in the collection will be used as label for the Nx and Size plots.
Outputs
- Nx plot
- Size plot
This workflow takes as input a SRA_manifest from SRA Run Selector and will generate one fastq file or fastq pair of file for each experiment (concatenated multiple runs if necessary). Output will be relabelled to match the column specified by the user.
Antimicrobial resistance gene detection from assembled bacterial genomes
Type: Galaxy
Creators: ABRomics , Pierre Marin, Pierre Marin, abromics-consortium
Submitter: WorkflowHub Bot
Assembly of bacterial paired-end short read data with generation of quality metrics and reports
Type: Galaxy
Creators: ABRomics , Pierre Marin, Clea Siguret, abromics-consortium
Submitter: WorkflowHub Bot
Short paired-end read analysis to provide quality analysis, read cleaning and taxonomy assignation
Type: Galaxy
Creators: ABRomics , Pierre Marin, Clea Siguret, abromics-consortium
Submitter: WorkflowHub Bot
This workflow takes as input a list of paired-end fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously as well as normalized coverage (per million mapped reads) on uniquely mapped reads. The counts are reprocessed to be similar to HTSeq-count output. FPKM are computed with cufflinks and/or with StringTie. The unstranded normalized coverage is computed with bedtools.
This workflow take as input a collection of paired fastq. Remove adapters with cutadapt, map pairs with bowtie2 allowing dovetail. Keep MAPQ30 and concordant pairs. BAM to BED. MACS2 with "ATAC" parameters.
This workflow takes as input a collection of paired fastqs. Remove adapters with cutadapt, map pairs with bowtie2. Keep MAPQ30 and concordant pairs. MACS2 for paired bam.
This workflow takes as input a collection of fastqs (single reads). Remove adapters with cutadapt, map with bowtie2. Keep MAPQ30. MACS2 for bam with fixed extension or model.
This workflow takes as input a collection of paired fastq. It will remove bad quality and adapters with cutadapt. Map with Bowtie2 end-to-end. Will remove reads on MT and unconcordant pairs and pairs with mapping quality below 30 and PCR duplicates. Will compute the pile-up on 5' +- 100bp. Will call peaks and count the number of reads falling in the 1kb region centered on the summit. Will compute 2 normalization for coverage: normalized by million reads and normalized by million reads in peaks. ...
This workflow takes as input a list of single-reads fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously as well as normalized coverage (per million mapped reads) on uniquely mapped reads. The counts are reprocessed to be similar to HTSeq-count output. FPKM are computed with cufflinks and/or with StringTie. The unstranded normalized coverage is computed with bedtools.
Microbiome - Taxonomy Profiling
Nanopore datasets analysis - Phylogenetic Identification - antibiotic resistance genes detection and contigs building
Microbiome - Variant calling and Consensus Building