EI Single-Cell Analysis pipeline

master @ 60d6da5 (earliest)

• master @ 63ffb68 (latest)
  
• master @ 60d6da5 (earliest)
  

Introduction

EarlhamInst/eisca is a bioinformatics pipeline that performs analysis for single-cell RNA-seq data. The pipeline is built using Nextflow. The pipeline was developed as a generalized, flexible, and scalable workflow for scRNA-seq analysis. It is primarily designed for droplet-based (10x) and plate-based (Smart-seq2) data. The pipeline can be applied from multiple starting points, either from raw FASTQ data or single-cell AnnData for the specified analysis phase.

The modules of the pipeline are listed as follows:

• Primary analysis
  • FastQC - Raw read QC
  • TrimGalore - Adapter and quality trimming to FastQ files
  • Kallisto & Bustools - Mapping & quantification by Kallisto & Bustools
  • Salmon Alevin - Mapping & quantification by Salmon Alevin
  • STARsolo - Mapping & quantification by STAR
  • MTX conversion - Converting count matrixes into Anndata objects
  • CONCAT counts - Concatenating input Anndata objects into one Anndata object
• Secondary analysis
  • QC & cell filtering - cell filtering and QC on raw data and filtered data
  • Clustering analysis - single-cell clustering analysis
  • Merging/integration of samples
• Tertiary analysis
  • Cell type annotation
  • Differential expression analysis
  • Cell-cell communication analysis
  • Trajectory & pseudotime analysis (to be implemented)
  • Other downstream analyses (to be implemented)
• Pipeline reporting
  • Analysis report - Single-ell Analysis Report.
  • MultiQC - Aggregate report describing results and QC for tools registered in nf-core
  • Pipeline information - Report metrics generated during the workflow execution

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

sample,fastq_1,fastq_2
pbmc8k,pbmc8k_S1_L007_R1_001.fastq.gz,pbmc8k_S1_L007_R2_001.fastq.gz
pbmc8k,pbmc8k_S1_L008_R1_001.fastq.gz,pbmc8k_S1_L008_R2_001.fastq.gz
pbmc5k,pbmc5k_S1_L003_R1_001.fastq.gz,pbmc5k_S1_L003_R2_001.fastq.gz

Each row represents a fastq file (single-end) or a pair of fastq files (paired end).

Now, you can run the pipeline using:

nextflow run TGAC/eisca \
   -profile  \
   --input samplesheet.csv \
   --genome_fasta GRCm38.p6.genome.chr19.fa \
   --gtf gencode.vM19.annotation.chr19.gtf \
   --protocol 10XV2 \
   --aligner  \
   --outdir 

[!WARNING] Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/eisca was originally written by Huihai Wu.

We thank the following people for their extensive assistance in the development of this pipeline:

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 #eisca channel (you can join with this invite).

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.