Synopsis

The human body contains a countless variety and diversity of cell types, states, and interactions. We wish to understand these tissues and the cell types at much deeper level. Single-cell RNA-seq (scRNA-seq) offers a look into what genes are being expressed at the level of individual cells. Overall this method allows one to identify cell types, find rare or unidentified cell types or states, identify genes that are differently expressed in different cell types, and explore changes in expression whilst including spatial, regulatory, and protein interactions.

We hope that others would find use for this transcript_structure generator that allows one to take input gtf-files of specific gene transcripts and outputs a gtf-file containing intron/exon structures per input transcript. Moreover, one can specify a probability for intron-inclusion which is used to simulate incorrect splicing.

Installation

To install the Python virtual environment, run

conda env create --file environment.yml
conda activate transcript-structure-generator

Usage

Input:

• csv-formatted file ("ID,Count") with counts for individual transcripts
• probability of intron inclusion (float in range [0,1])
• gtf-formatted file with exon coordinates of the transcripts included in the csv file

Output:

• gtf-formatted file containing generated intron/exon structures per transcript
• csv-formatted file ("NewTranscriptID,ID,Count") with
  • id of generated transcript
  • id of original transcript (without intron inclusions)
  • count

To install package, run

pip install setuptools>=62.1.0
pip install .

To generate the sampled transcripts, open a new shell, activate your environment and run

conda activate transcript-structure-generator

transcript-generator --transcripts <transcripts_file> --annotation <annotations_file> --prob_inclusion=<probability_inclusion> [--log "INFO"]

where the transcripts file should be csv-formatted, the annotation file gtf-formatted and the inclusion probability for introns a float in the range [0,1]. The log parameter is optional and can be one of ["CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"]. The default is INFO.

Development

To perform all tests, make sure your environment corresponds to the environment.yml file and run

pytest tests

License

MIT license, Copyright (c) 2021 Zavolan Lab, Biozentrum, University of Basel

Contributers

Larissa Glass
Michael Zimmermann
Andri Fraenkl