HLAQuant - Get HLA allele specific expression
Author: Austin Crinklaw
What is it?
HLAQuant is a pipeline that produces fast and accurate allele specific expression for HLA genes. This is done by quantifying on the peptide binding groove domain using Salmon with personalized sequences.
- Linux OS
- NCBI Blast+
- Salmon -- please ensure Salmon is on your PATH!
- Python 3+
- Python packages: Pandas, BioPython
How to use:
HLAQuant can be downloaded through PyPI using the following pip command.
pip install hlaquant
HLAQuant takes two input files currently.
- File one (-hla) consists of a sample_id and then a list of alleles corresponding to that sample's typing (tab separated)
- File two (-fastq) consists of a sample_id and then a list of FASTQ files corresponding to that sample (paired-end or single-end) Examples of these inputs can be found under the 'test_data/' directory
- A list of parameters and their descriptions can be found with the -h flag
python -m HLAQuant -h
The output will match that of Salmons. It consists of a tab separated file containing the transcript ID (in this case, a specific HLA allele), as well as the number of reads. TPMs can be ignored as they will be inaccurate since we are only quantifying over a few sequences.
How does it work?
- We first take the list of alleles and fetch the corresponding sequences from IMGT
- Next we extract the sequences corresponding to their groove domains from these sequences
- We build an index for quantification using these G-domain sequences
- We then perform quantification using this index
The paper outlining this method in detail can be found [....somewhere when it is published]
This pipeline would be unable to work without Salmon
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.
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