nfcore/smrnaseq repository overview

⁠Introduction

nf-core/smrnaseq is a bioinformatics best-practice analysis pipeline used for small RNA sequencing data.

The pipeline is built using Nextflow⁠, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

⁠Quick Start

1. Install nextflow⁠ (>=20.04.0)

2. Install any of Docker⁠, Singularity⁠, Podman⁠, Shifter⁠ or Charliecloud⁠ for full pipeline reproducibility (please only use Conda⁠ as a last resort; see docs⁠)

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run nf-core/smrnaseq -profile test,<docker/singularity/podman/shifter/charliecloud/conda/institute>
   

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   Please check nf-core/configs⁠ to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

4. Start running your own analysis!

   nextflow run nf-core/smrnaseq -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37
   

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See usage docs⁠ for all of the available options when running the pipeline.

⁠Pipeline summary

1. Raw read QC (FastQC⁠)
2. Adapter trimming (Trim Galore!⁠)
   1. Insert Size calculation
   2. Collapse reads (seqcluster⁠)
3. Alignment against miRBase mature miRNA (Bowtie1⁠)
4. Alignment against miRBase hairpin
   1. Unaligned reads from step 3 (Bowtie1⁠)
   2. Collapsed reads from step 2.2 (Bowtie1⁠)
5. Post-alignment processing of miRBase hairpin
   1. Basic statistics from step 3 and step 4.1 (SAMtools⁠)
   2. Analysis on miRBase hairpin counts (edgeR⁠)
      • TMM normalization and a table of top expression hairpin
      • MDS plot clustering samples
      • Heatmap of sample similarities
   3. miRNA and isomiR annotation from step 4.1 (mirtop⁠)
6. Alignment against host reference genome (Bowtie1⁠)
   1. Post-alignment processing of alignment against host reference genome (SAMtools⁠)
7. Novel miRNAs and known miRNAs discovery (MiRDeep2⁠)
   1. Mapping against reference genome with the mapper module
   2. Known and novel miRNA discovery with the mirdeep2 module
8. miRNA quality control (mirtrace⁠)
9. Present QC for raw read, alignment, and expression results (MultiQC⁠)

⁠Documentation

The nf-core/smrnaseq pipeline comes with documentation about the pipeline: usage⁠ and output⁠.

⁠Credits

nf-core/smrnaseq was originally written for use at the National Genomics Infrastructure⁠ at SciLifeLab⁠ in Stockholm, Sweden, by Phil Ewels (@ewels), Chuan Wang (@chuan-wang) and Rickard Hammarén (@Hammarn). Updated by Lorena Pantano (@lpantano) from MIT.

⁠Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines⁠.

For further information or help, don't hesitate to get in touch on the Slack #smrnaseq channel⁠ (you can join with this invite⁠).

⁠Citations

You can cite the nf-core publication as follows:

In addition, references of tools and data used in this pipeline are as follows: