gene_annot

snakemake pipeline from transcripts to annotated protein sequences

About

This is a snakemake wrapper of a number of well-known, standardised tools to annotate a dataset of transcripts based on sequence-homology and protein domain methods.

What it does

Briefly, this workflow will extract the longest coding sequences per transcript (longest isoform per gene) from a genome annotation. It will translate these to proteins, and proceed with a multi-evidence functional annotation (EggNOG mapper, interproscan, blast best reciprocal hits, and Orthofinder). If needed, the pipeline will download and prepare the necessary databases for these steps.

Eventually the pipeline will aim at generating two final output files; one with the functional annotation of all the predicted protein-coding genes, and one with the functional annotation of a subset of the genes with high-confidence of being a transcription factor.

The user will be able to proceed with downstream analyses of their own and to use any of the intermediate or secondarily derived outputs of this workflow.

Input

The necessar input to run this workflow is:

• A .fasta file of a genome of interest,
• A .gtf annotation of the genes of the genome of interest,
• A config.yaml file with all the necessary parameters, specificially:
  • A name of the organism (this will eventually be used to tag all the files in the run),
  • The path to the genome of interest,
  • The path to the gtf of interest,
  • Parameters for the different tools (otherwise the workflow will use the ones specified by default)

The user can use the pre-included config.yaml file as a template for their own run.

Alternatively, the user can provide a set of transcripts in a transcripts.fna file at the root directory of the workflow or a set of protein sequences in the path transdecoder/predicted.pep. Snakemake will recognise these and start the workflow from these files.

How to run

NOTE: At the moment the workflow uses checkpoints (empty files whose names are recognised by snakemake) as a means to connect rules. If one whishes to restart the workflow or resume from a specific step, please consider removing the checkpoints/ directory or any specific checkpoint of interest.

First of all make sure that you have snakemake and conda accessible from your running environment. You can always create a conda environment with snakemake in it (this is how I do it myself).

# create venv
mamba create -n snakemake_venv -c bioconda snakemake

# activate venv
conda activate snakemake_venv

After cloning this repository, prepare the config file and the genome and annotation files.

Then, move to the root directory of the workflow and run snakemake like this

# move to the directory of the workflow
cd gene_annot/

# run snakemake
snakemake --use-conda

Optionally you can add options like --cores NUMCORES to use a specific amount of cores, and --rerun-incomplete to retry and re-run the steps that might have gone wrong in a previous attempt. Please refer to the snakemake documentation for more information.