jvfe/tcruzi_gene_exp is a bioinformatics pipeline to preprocess and extract T. cruzi gene expression data

1. Read QC (FastQC)
2. fastp for read pre-processing (fastp)
3. Kraken2 for extracting only protozoa reads (kraken2)
4. HiSat2 and STAR for sequence alignment
5. SubRead for read quantification

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,single_end
CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_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 jvfe/tcruzi_gene_exp \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --fasta <reference_fasta_file> \
   --gtf <reference_gtf_file> \
   --kraken2_db <eupath_kraken2db.tar.gz> \
   --outdir <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.

jvfe/tcruzi_gene_exp was originally written by João Cavalcante (@jvfe) and Iara de Souza (@iaradsouza1).

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

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

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

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.