Nextflow Modules
Showing module(s) with keyword "bayesian"
| Module | Kind | Keywords | Description |
|---|---|---|---|
| nf-core/fasta_gtf_bam_rpbp | Workflow | rpbp orf bayesian translation riboseq | End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data with Rp-Bp (Malone et al. 2017). Ribo-seq sequences the short mRNA footprints protected by translating ribosomes; Rp-Bp uses a Bayesian model to score which open reading frames (ORFs) on the transcriptome show the characteristic 3-nucleotide periodicity of active translation. Given a genome FASTA, annotation GTF and one or more pre-aligned Ribo-seq BAMs, the subworkflow: 1. Builds the per-ORF reference (rpbp/preparegenome) once per run - enumerates candidate ORFs from the GTF. 2. For each sample, builds per-read-length metagene profiles around annotated start codons (extract-metagene-profiles), scores their three-nucleotide periodicity with Bayesian models (estimate-metagene-profile-bayes-factors), picks the best P-site offset per periodic read length (select-periodic-offsets), and filters down to the high-confidence read-length/offset pairs that will drive ORF-level scoring (get-periodic-lengths-offsets). 3. Builds per-ORF P-site count vectors with those selected offsets (extract-orf-profiles), scores each ORF as "translated" vs "untranslated" with a Bayesian model (estimate-orf-bayes-factors), and emits the final filtered set of predicted translated ORFs as BED + DNA FASTA + protein FASTA (select-final-prediction-set). Each Rp-Bp step is a separate Nextflow process so `-resume` only re-runs what changed, and STAR/bowtie alignment is supplied via the BAM input (this subworkflow does not realign). |
| nf-core/freebayes | Process | variant caller SNP genotyping somatic variant calling germline variant calling bacterial variant calling bayesian | A haplotype-based variant detector |
| nf-core/leehom | Process | ancient DNA adapter removal clipping trimming merging collapsing preprocessing bayesian | Bayesian reconstruction of ancient DNA fragments |