YeastI

Introduction

This package contains a set of minimal eukaryotic genome and transcriptome datasets from chromosme I of Saccharomyces cerevisiae. They may, for example, be useful for rapidly testing a RNA-seq bioinformatics pipeline.

Installation

Ensure your computing environment includes Python 3.11 or later and the following bioinformatics tools:

• sra-tools
• pigz
• fastp
• kraken2

Conda is useful for setting up this environment. Then, YeastI can be installed with Pip:

conda create -c conda-forge -c bioconda -n yeasti \
  biopython pysradb sra-tools pigz fastp kraken2
conda activate yeasti
pip install yeasti

Usage

Run yeasti without arguments to list the help text of all subcommands

yeasti

usage: yeasti [-h] [--version] {init,path,metadata,download,sheet,trim,classify} ...

Small dataset of yeast chromosome 1

positional arguments:
  {init,path,metadata,download,sheet,trim,classify}
    init                fully initialize the dataset by downloading, trimming, and classifying RNA-seq reads
    path                show paths to data directory and files
    metadata            fetch sra metadata
    download            download RNA-seq reads
    sheet               sample sheet for yeasti rna-seq dataset
    trim                trim downloaded reads
    classify            classify downloaded reads

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit

To download and downsample all RNA-seq data, run:

yeasti init

Use yeasti path to get the absolute path for a data file

yeasti path data-dir
yeasti path genome
yeasti path cds
yeasti path pep
yeasti path gff
yeasti path gtf
yeasti path sheet

To see the sample sheet listing the locations of the RNA-seq reads:

yeasti sheet

If you need the data at another location, you can symbolically link to the YeastI dataset, or copy the contents to another directory

ln -s `yeasti path data-dir` test_data/
cp -r `yeasti path data-dir` test_data/

To see the SRA metadata of the RNA-seq reads:

yeasti metadata

To execute the initialization steps individually:

yeasti download
yeasti trim
yeasti classify

Datasets

There are two groups of datasets:

1. The directly included package data of chromosome I sequence and annotation from assembly R64-1-1 at Ensembl, including:
   • Genome sequence (FASTA)
   • Coding sequences (FASTA)
   • Peptide sequences (FASTA)
   • Gene annotation (GFF3, GTF)
2. The RNA-seq reads from Prigent et al. (2024), which are downloaded from SRA/NCBI BioProject PRJNA842028 and downsampled to include only chromosome I reads by running an included script.
   • The study sequenced mRNA from S. cerevisiae under sulfur starvation at four timepoints with three replicates each, but only two of the timepoints are included in YeastI (T0 and T120).
   • Other similar dataset references can also be found at the Saccharomyces Genome Database.

Downsampling RNA-seq

During the initialization process, after the RNA-seq reads are downloaded they are downsampled by:

1. Adapter and quality trimming with fastp
2. Classification with kraken2 to filter out all reads that do not match chromosome I

Configuration

You can configure some YEASTI settings using environment variables or a TOML file.

Environment variables

export YEASTI_DOWNLOAD_DIR = /absolute/path/to/directory/
export YEASTI_TAXID = <integer>
export YEASTI_SAMPLE_SHEET = /absolute/path/to/sample_sheet.csv
export YEASTI_KRAKEN2_DB /absolute/path/to/kraken2_db/

Config file

By default, YeastI looks for configuration in TOML format at $HOME/.yeasti.toml

download_dir = /absolute/path/to/directory/
taxid = <integer>
sample_sheet = /absolute/path/to/sample_sheet.csv
kraken2_db = /absolute/path/to/kraken2_db/

The location of the config file can also be set using an environment variable:

export YEASTI_CONFIG_FILE=/absolute/path/to/alternate/config.toml

Python API

YeastI resources can also be accessed from within python:

import yeasti
yeasti.init()
yeasti.path('genome')
metadata = yeasti.metadata()
sample_sheet = yeasti.create_sample_sheet(metadata)
yeasti.write_sample_sheet(sample_sheet, 'sample_sheet.csv')
yeasti.download()
yeasti.trim('reads_1.fastq.gz', 'reads_2.fastq.gz')
yeasti.classify('reads_1.fastq.gz', 'reads_2.fastq.gz')