nf-core pipeline · differential-expression, lncrna, long-non-coding
nf-core/lncpipe
A bioinformatics pipeline for analysing long non-coding RNAs from RNA sequencing datasets.
What nf-core/lncpipe is
nf-core/lncpipe is a bioinformatics pipeline designed to analyse long non-coding RNAs (lncRNAs) from RNA sequencing (RNA-seq) datasets. The workflow was originally created by Qi Zhao as part of the nf-core community.
The pipeline focuses on non-coding RNA and transcriptome investigations, including differential expression analysis across sequencing experiments.
What the pipeline does
The pipeline ingests single-end or paired-end sequencing reads supplied through a comma-separated samplesheet. It executes raw read quality control using FastQC and collates quality assessment results into an aggregated report with MultiQC.
Key facts
- Original author
- Qi Zhao
- Development status
- Under development
- Primary application
- Long non-coding RNA analysis and differential expression
- Input formats
- Single-end or paired-end FASTQ files via CSV samplesheet
- Included tools
- FastQC, MultiQC
What you can use it for
- Long non-coding RNA profiling
- Analysing long non-coding RNA elements across transcriptomic sequencing datasets.
- Differential expression studies
- Evaluating differential expression of non-coding transcripts across experimental samples.
- RNA-seq read quality control
- Checking sequencing quality with FastQC and compiling summary metrics using MultiQC.
Run it here
The research agent runs nf-core/lncpipe 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
- Integrates standard read quality control using FastQC alongside MultiQC reporting.
- Accepts both single-end and paired-end sequencing read arrangements.
Watch out for
- The pipeline is explicitly marked as under development.
- Documented workflow steps beyond quality control are currently incomplete.
Questions
Can I run nf-core/lncpipe without my own cluster?
The research agent runs nf-core/lncpipe 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/lncpipe under?
MIT, like every nf-core pipeline.
What inputs does the pipeline accept?
The pipeline accepts single-end or paired-end FASTQ files specified within a samplesheet in CSV format.
Who created nf-core/lncpipe?
The pipeline was originally written by Qi Zhao.
Which quality control tools are included in the pipeline?
Raw read quality checks are carried out by FastQC, and quality reports are aggregated using MultiQC.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/lncpipe's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.