nf-core¶
nf-core is a collection of analysis pipelines built using Nextflow.
For more information, check here.
Supported pipelines¶
Pipeline |
Release |
Description |
|---|---|---|
|
|
B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framework |
|
|
16S rRNA amplicon sequencing analysis workflow using QIIME2 |
|
|
ATAC-seq peak-calling, QC and differential analysis pipeline |
|
|
Simple bacterial assembly and annotation pipeline |
|
|
A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences |
|
|
CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags |
|
|
ChIP-seq peak-calling, QC and differential analysis pipeline |
|
|
CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling options |
|
|
Coprolite host Identification pipeline |
|
|
Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis |
|
|
A Nextflow pipeline for running the Google DeepVariant variant caller. |
|
|
Automated quantitative analysis of DIA proteomics mass spectrometry measurement |
|
|
Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq |
|
|
A fully reproducible and state-of-the-art ancient DNA analysis pipeline |
|
|
A bioinformatics best-practice analysis pipeline for epitope prediction and annotation |
|
|
Pipeline to fetch metadata and raw FastQ files from public and private databases |
|
|
Analysis of Chromosome Conformation Capture data (Hi-C) |
|
|
Precision HLA typing from next-generation sequencing data |
|
|
Image Mass Cytometry analysis pipeline |
|
|
Assembly and binning of metagenomes |
|
|
Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data |
|
|
Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark or bwa-meth + MethylDackel |
|
|
Identify and quantify MHC eluted peptides from mass spectrometry raw |
|
|
Nanopore demultiplexing, QC and alignment pipeline |
|
|
Nascent transcription processing pipeline |
|
|
De novo assembly pipeline for 10X linked-reads using Supernova |
|
|
The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis |
|
|
Proteomics label-free quantification (LFQ) analysis pipeline |
|
|
RNA-seq analysis pipeline for detection gene-fusions |
|
|
RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control |
|
|
Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing |
|
|
A single-cell RNAseq pipeline for 10X genomics data |
|
|
SLAMSeq processing and analysis pipeline |
|
|
A small-RNA sequencing analysis pipeline |
|
|
Assembly and intrahost/low-frequency variant calling for viral samples |
Dependencies¶
For information on how to use the Dependencies parameter, please refer to the Initialization - Bash script section of the documentation.
Create a Conda environment¶
The user can also install the required software dependencies via Conda by specifyifg the packages or the path(s) to the configuration YAML file(s) directly in the pipeline script.
In this case the user must use the option --enable_conda.
Interactive mode¶
The Interactive mode parameter is used to start an interactive job session where the user can open a terminal window from the job progress page and execute shell commands.
Pipelines are executed as follows:
$ nextflow run ~/nf-core-<pipeline>-<release>/workflow/ --max_cpus $CORES --max_memory $MEMORY <options>
where $CORES and $MEMORY correspond to the maximum number of cores and total memory of the selected machine type.
Contents