Cargando…
RNA2HLA: HLA-based quality control of RNA-seq datasets
RNA-sequencing (RNA-seq) is a widely used approach for accessing the transcriptome in biomedical research. Studies frequently include multiple samples taken from the same individual at various time points or under different conditions, correct assignment of those samples to each particular participa...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425422/ https://www.ncbi.nlm.nih.gov/pubmed/33758920 http://dx.doi.org/10.1093/bib/bbab055 |
_version_ | 1783749846817046528 |
---|---|
author | Chelysheva, Irina Pollard, Andrew J O’Connor, Daniel |
author_facet | Chelysheva, Irina Pollard, Andrew J O’Connor, Daniel |
author_sort | Chelysheva, Irina |
collection | PubMed |
description | RNA-sequencing (RNA-seq) is a widely used approach for accessing the transcriptome in biomedical research. Studies frequently include multiple samples taken from the same individual at various time points or under different conditions, correct assignment of those samples to each particular participant is evidently of great importance. Here, we propose taking advantage of typing the highly polymorphic genes from the human leukocyte antigen (HLA) complex in order to verify the correct allocation of RNA-seq samples to individuals. We introduce RNA2HLA, a novel quality control (QC) tool for performing study-wide HLA-typing for RNA-seq data and thereby identifying the samples from the common source. RNA2HLA allows precise allocation and grouping of RNA samples based on their HLA types. Strikingly, RNA2HLA revealed wrongly assigned samples from publicly available datasets and thereby demonstrated the importance of this tool for the quality control of RNA-seq studies. In addition, our tool successfully extracts HLA alleles in four-digital resolution and can be used to perform massive HLA-typing from RNA-seq based studies, which will serve multiple research purposes beyond sample QC. |
format | Online Article Text |
id | pubmed-8425422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84254222021-09-09 RNA2HLA: HLA-based quality control of RNA-seq datasets Chelysheva, Irina Pollard, Andrew J O’Connor, Daniel Brief Bioinform Problem Solving Protocol RNA-sequencing (RNA-seq) is a widely used approach for accessing the transcriptome in biomedical research. Studies frequently include multiple samples taken from the same individual at various time points or under different conditions, correct assignment of those samples to each particular participant is evidently of great importance. Here, we propose taking advantage of typing the highly polymorphic genes from the human leukocyte antigen (HLA) complex in order to verify the correct allocation of RNA-seq samples to individuals. We introduce RNA2HLA, a novel quality control (QC) tool for performing study-wide HLA-typing for RNA-seq data and thereby identifying the samples from the common source. RNA2HLA allows precise allocation and grouping of RNA samples based on their HLA types. Strikingly, RNA2HLA revealed wrongly assigned samples from publicly available datasets and thereby demonstrated the importance of this tool for the quality control of RNA-seq studies. In addition, our tool successfully extracts HLA alleles in four-digital resolution and can be used to perform massive HLA-typing from RNA-seq based studies, which will serve multiple research purposes beyond sample QC. Oxford University Press 2021-03-24 /pmc/articles/PMC8425422/ /pubmed/33758920 http://dx.doi.org/10.1093/bib/bbab055 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Problem Solving Protocol Chelysheva, Irina Pollard, Andrew J O’Connor, Daniel RNA2HLA: HLA-based quality control of RNA-seq datasets |
title | RNA2HLA: HLA-based quality control of RNA-seq datasets |
title_full | RNA2HLA: HLA-based quality control of RNA-seq datasets |
title_fullStr | RNA2HLA: HLA-based quality control of RNA-seq datasets |
title_full_unstemmed | RNA2HLA: HLA-based quality control of RNA-seq datasets |
title_short | RNA2HLA: HLA-based quality control of RNA-seq datasets |
title_sort | rna2hla: hla-based quality control of rna-seq datasets |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425422/ https://www.ncbi.nlm.nih.gov/pubmed/33758920 http://dx.doi.org/10.1093/bib/bbab055 |
work_keys_str_mv | AT chelyshevairina rna2hlahlabasedqualitycontrolofrnaseqdatasets AT pollardandrewj rna2hlahlabasedqualitycontrolofrnaseqdatasets AT oconnordaniel rna2hlahlabasedqualitycontrolofrnaseqdatasets |