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Transcriptome diversity is a systematic source of variation in RNA-sequencing data
RNA sequencing has been widely used as an essential tool to probe gene expression. While standard practices have been established to analyze RNA-seq data, it is still challenging to interpret and remove artifactual signals. Several biological and technical factors such as sex, age, batches, and sequ...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982896/ https://www.ncbi.nlm.nih.gov/pubmed/35324895 http://dx.doi.org/10.1371/journal.pcbi.1009939 |
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author | García-Nieto, Pablo E. Wang, Ban Fraser, Hunter B. |
author_facet | García-Nieto, Pablo E. Wang, Ban Fraser, Hunter B. |
author_sort | García-Nieto, Pablo E. |
collection | PubMed |
description | RNA sequencing has been widely used as an essential tool to probe gene expression. While standard practices have been established to analyze RNA-seq data, it is still challenging to interpret and remove artifactual signals. Several biological and technical factors such as sex, age, batches, and sequencing technology have been found to bias these estimates. Probabilistic estimation of expression residuals (PEER), which infers broad variance components in gene expression measurements, has been used to account for some systematic effects, but it has remained challenging to interpret these PEER factors. Here we show that transcriptome diversity–a simple metric based on Shannon entropy–explains a large portion of variability in gene expression and is the strongest known factor encoded in PEER factors. We then show that transcriptome diversity has significant associations with multiple technical and biological variables across diverse organisms and datasets. In sum, transcriptome diversity provides a simple explanation for a major source of variation in both gene expression estimates and PEER covariates. |
format | Online Article Text |
id | pubmed-8982896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89828962022-04-06 Transcriptome diversity is a systematic source of variation in RNA-sequencing data García-Nieto, Pablo E. Wang, Ban Fraser, Hunter B. PLoS Comput Biol Research Article RNA sequencing has been widely used as an essential tool to probe gene expression. While standard practices have been established to analyze RNA-seq data, it is still challenging to interpret and remove artifactual signals. Several biological and technical factors such as sex, age, batches, and sequencing technology have been found to bias these estimates. Probabilistic estimation of expression residuals (PEER), which infers broad variance components in gene expression measurements, has been used to account for some systematic effects, but it has remained challenging to interpret these PEER factors. Here we show that transcriptome diversity–a simple metric based on Shannon entropy–explains a large portion of variability in gene expression and is the strongest known factor encoded in PEER factors. We then show that transcriptome diversity has significant associations with multiple technical and biological variables across diverse organisms and datasets. In sum, transcriptome diversity provides a simple explanation for a major source of variation in both gene expression estimates and PEER covariates. Public Library of Science 2022-03-24 /pmc/articles/PMC8982896/ /pubmed/35324895 http://dx.doi.org/10.1371/journal.pcbi.1009939 Text en © 2022 García-Nieto et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article García-Nieto, Pablo E. Wang, Ban Fraser, Hunter B. Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title | Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title_full | Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title_fullStr | Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title_full_unstemmed | Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title_short | Transcriptome diversity is a systematic source of variation in RNA-sequencing data |
title_sort | transcriptome diversity is a systematic source of variation in rna-sequencing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982896/ https://www.ncbi.nlm.nih.gov/pubmed/35324895 http://dx.doi.org/10.1371/journal.pcbi.1009939 |
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