CressChrom1

Introduction

This package contains a set of minimal eukaryotic genome and transcriptome datasets from chromosme 1 of Arabidopsis thaliana. 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
• openpyxl

Conda is useful for setting up this environment. Then, cresschrom1 can be installed with Pip:

conda create -c conda-forge -c bioconda -n cresschrom1 \
  biopython pysradb sra-tools pigz fastp kraken2 openpyxl
conda activate cresschrom1
pip install cresschrom1

Usage

Run cresschrom1 without arguments to list the help text of all subcommands

cresschrom1

usage: cresschrom1 [-h] [--version] {init,path,metadata,download,sheet,trim,classify} ...

Small dataset of Arabidopsis 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 cresschrom1 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:

cresschrom1 init

Use cresschrom1 path to get the absolute path for a data file

cresschrom1 path data-dir
cresschrom1 path genome
cresschrom1 path cds
cresschrom1 path pep
cresschrom1 path gff
cresschrom1 path gtf
cresschrom1 path sheet

cresschrom1 path can also fetch paths to datasets for the two alternate species:

cresschrom1 path genome-atha
cresschrom1 path genome-aare

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

cresschrom1 sheet

If you need the data at another location, you can symbolically link to the cresschrom1 dataset, or copy the contents to another directory

ln -s `cresschrom1 path data-dir` test_data/
cp -r `cresschrom1 path data-dir` test_data/

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

cresschrom1 metadata

To execute the initialization steps individually:

cresschrom1 download
cresschrom1 trim
cresschrom1 classify

Datasets

There are two groups of datasets:

1. The directly included package data of chromosome 1 sequence and annotation from A. thaliana assembly TAIR10 at NCBI, including:
   • Genome sequence (FASTA)
   • Coding sequences (FASTA)
   • mRNA transcripts (FASTA)
   • Peptide sequences (FASTA)
   • Gene annotation (GFF3, GTF)
   • Sequences and annotations are also included for another Arabidopsis species, A. arenosa. Two additional recent genome asseblies of A. arenosa and A. lyrata, which were published in Bramsiepe et al. (2023), are also included. The A. arenosa and A. lyrata assemblies are restricted to chromosomes 1 and 2, which are colinear with A. thaliana's chromosome 1.
2. The RNA-seq reads are from a curated list published by from Shintani et al. (2024). They are downloaded from SRA/NCBI and downsampled to include only chromosome 1 reads by running an included script.

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 cresschrom1 settings using environment variables or a TOML file.

Environment variables

export cresschrom1_DOWNLOAD_DIR = /absolute/path/to/directory/
export cresschrom1_TAXID = <integer>
export cresschrom1_SAMPLE_SHEET = /absolute/path/to/sample_sheet.csv
export cresschrom1_KRAKEN2_DB /absolute/path/to/kraken2_db/

Config file

By default, cresschrom1 looks for configuration in TOML format at $HOME/.cresschrom1.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 cresschrom1_CONFIG_FILE=/absolute/path/to/alternate/config.toml

Python API

cresschrom1 resources can also be accessed from within python:

import cresschrom1
cresschrom1.init()
cresschrom1.path('genome')
cresschrom1.path('genome-aare')
metadata = cresschrom1.metadata()
sample_sheet = cresschrom1.create_sample_sheet(metadata)
cresschrom1.write_sample_sheet(sample_sheet, 'sample_sheet.csv')
cresschrom1.download()
cresschrom1.trim('reads_1.fastq.gz', 'reads_2.fastq.gz')
cresschrom1.classify('reads_1.fastq.gz', 'reads_2.fastq.gz')
cresschrom1.taxid
cresschrom1.busco

Example usage with nf-core pipelines

Conda environment

conda create -c conda-forge -c bioconda -n cresschrom1-nf-core \
  biopython pysradb sra-tools pigz fastp kraken2 openpyxl \
  nextflow nf-core
conda activate cresschrom1-nf-core
pip install cresschrom1

nf-core/genomeqc

echo '{"is_plant": true, "skip_busco": false, "skip_tidk": false}' > genomeqc-params.json
cresschrom1 sheet --pipeline nf-core-genomeqc > sample_sheet.csv
nextflow run nf-core/genomeqc -r 1.0.1 \
  -profile <docker/singularity/.../institute> \
  -params-file genomeqc-params.json \
  --input sample_sheet.csv \
  --outdir genomeqc_output_dir/ \
  --busco_lineage `cresschrom1 busco`

nf-core/seqinspector

cresschrom1 sheet --pipeline nf-core-seqinspector > sample_sheet.csv
nextflow run nf-core/seqinspector \
  -profile <docker/singularity/.../institute> \
  --input sample_sheet.csv \
  --outdir seqinspector_output_dir/ \
  --fasta `cresschrom1 path genome`

nf-core/rnaseq

cresschrom1 sheet > sample_sheet.csv
nextflow run nf-core/rnaseq \
  -profile <docker/singularity/.../institute> \
  --input sample_sheet.csv \
  --outdir rnaseq_output_dir/ \
  --fasta `cresschrom1 path genome` \
  --gtf `cresschrom1 path gtf`

nf-core/denovotranscript

cresschrom1 sheet > sample_sheet.csv
nextflow run nf-core/denovotranscript -r 1.2.1 \
  -profile <docker/singularity/.../institute> \
  --input sample_sheet.csv \
  --outdir denovotranscript_output_dir/ \
  --assemblers rnaspades