nf-core pipeline · gro-seq, nascent, pro-seq
nf-core/nascent
A Nextflow pipeline for processing nascent transcript and transcriptional start site sequencing assays.
What nf-core/nascent is
nf-core/nascent is a bioinformatics analysis pipeline designed for processing nascent transcript and transcriptional start site (TSS) sequencing assays, such as GRO-seq and PRO-seq. It was originally authored by Ignacio Tripodi and Margaret Gruca, and subsequently rewritten in Nextflow DSL2 by Edmund Miller and Sruthi Suresh at The University of Texas at Dallas.
Nascent RNA assays capture active transcription by sequencing nascent RNA rather than steady-state RNA pools. This pipeline provides a standardised, reproducible workflow to process raw sequencing reads into alignments, quality control summaries, genome coverage tracks, de novo transcript predictions, and feature quantifications.
What the pipeline does
The workflow begins by running FastQC for raw read quality assessment and fastp for adapter and quality trimming. Trimmed reads are aligned against a reference genome using either BWA, bwamem2, or DRAGMAP. Alignments are sorted and indexed using SAMtools. If unique molecular identifiers (UMIs) are present, deduplication is performed with UMI-tools; alternatively, duplicate reads are marked using Picard MarkDuplicates.
Post-alignment quality metrics are gathered using RSeQC, Preseq (for library complexity estimation), and BBMap (for sequencing coverage). BEDTools and deepTools generate normalised bedGraph and bigWig coverage tracks, respectively. Active nascent transcripts and TSS locations are detected using HOMER, GroHMM, and PINTS. Gene and nascent transcript abundances are then quantified using featureCounts, and all QC and processing metrics are collated into an interactive MultiQC report.
Key facts
- Workflow engine
- Nextflow (DSL2)
- Latest release
- 2.3.0 (2025-05-08)
- Assay types
- Nascent transcription (GRO-seq, PRO-seq) and TSS profiling
- Input formats
- Single-end or paired-end FASTQ files via CSV samplesheet
- Supported aligners
- BWA, bwamem2, DRAGMAP
- Transcript callers
- HOMER, GroHMM, PINTS
- Quantification tool
- featureCounts
- Coverage output formats
- bedGraph, bigWig
- Container support
- Docker, Singularity
What you can use it for
- GRO-seq and PRO-seq data processing
- End-to-end processing of nascent RNA sequencing data from raw reads through to alignment, coverage tracks, and gene-level quantification.
- Transcriptional start site (TSS) identification
- Identification and mapping of active transcription start sites and nascent transcript boundaries using PINTS, HOMER, and GroHMM.
- Nascent RNA quantification
- Quantifying newly synthesised RNA reads overlapping annotated genes and unannotated transcription units using featureCounts.
- Sequencing library quality evaluation
- Assessing library complexity with Preseq, RNA-specific sequencing metrics with RSeQC, and read depth distribution with BBMap and MultiQC.
Run it here
The research agent runs nf-core/nascent with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Supports multiple sequence alignment tools including BWA, bwamem2, and DRAGMAP.
- Handles both UMI-based deduplication with UMI-tools and optical or PCR duplicate marking with Picard MarkDuplicates.
- Integrates specialised nascent transcription discovery tools including HOMER, GroHMM, and PINTS.
- Employs isolated, per-process Docker and Singularity software containers through Nextflow DSL2 modules.
Watch out for
- Requires input FASTQ files to be specified in a structured CSV samplesheet format.
- Pipeline execution parameters must be provided via the command line or parameter files rather than custom configuration files.
Questions
Can I run nf-core/nascent without my own cluster?
The research agent runs nf-core/nascent with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/nascent under?
MIT, like every nf-core pipeline.
What sequencing assays can this pipeline analyse?
It is designed for nascent transcript (NT) and transcriptional start site (TSS) sequencing assays, such as PRO-seq and GRO-seq.
Which aligners are available in the pipeline?
Users can align reads using BWA, bwamem2, or DRAGMAP.
How are duplicated reads handled?
The pipeline supports UMI-based deduplication using UMI-tools, as well as general duplicate read marking using Picard MarkDuplicates.
Which tools are used for detecting nascent transcripts?
Transcript identification and TSS discovery are carried out using HOMER, GroHMM, and PINTS.
How to cite it
10.5281/zenodo.7245273
Written from nf-core/nascent's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.