RNA-seq is replacing microarrays as the primary tool for gene expression studies. Many RNA-seq studies have used insufficient biological replicates, resulting in low statistical power and inefficient use of sequencing resources.We show the explicit trade-off between more biological replicates and deeper sequencing in increasing power to detect differentially expressed (DE) genes. In the human cell line MCF7, adding more sequencing depth after 10 M reads gives diminishing returns on power to detect DE genes, whereas adding biological replicates improves power significantly regardless of sequencing depth. We also propose a cost-effectiveness metric for guiding the design of large-scale RNA-seq DE studies. Our analysis showed that sequencing less reads and performing more biological replication is an effective strategy to increase power and accuracy in large-scale differential expression RNA-seq studies, and provided new insights into efficient experiment design of RNA-seq studies.The code used in this paper is provided on: http://home.uchicago.edu/∼jiezhou/replication/. The expression data is deposited in the Gene Expression Omnibus under the accession ID GSE51403.
Описание
RNA-seq differential expression studies: more sequence or more replication? - PubMed - NCBI
%0 Journal Article
%1 Liu:2014:Bioinformatics:24319002
%A Liu, Y
%A Zhou, J
%A White, K P
%D 2014
%J Bioinformatics
%K experimental-design replicate rna-seq sequencing-depth statistics
%N 3
%P 301-304
%R 10.1093/bioinformatics/btt688
%T RNA-seq differential expression studies: more sequence or more replication?
%U https://www.ncbi.nlm.nih.gov/pubmed/24319002?dopt=Abstract
%V 30
%X RNA-seq is replacing microarrays as the primary tool for gene expression studies. Many RNA-seq studies have used insufficient biological replicates, resulting in low statistical power and inefficient use of sequencing resources.We show the explicit trade-off between more biological replicates and deeper sequencing in increasing power to detect differentially expressed (DE) genes. In the human cell line MCF7, adding more sequencing depth after 10 M reads gives diminishing returns on power to detect DE genes, whereas adding biological replicates improves power significantly regardless of sequencing depth. We also propose a cost-effectiveness metric for guiding the design of large-scale RNA-seq DE studies. Our analysis showed that sequencing less reads and performing more biological replication is an effective strategy to increase power and accuracy in large-scale differential expression RNA-seq studies, and provided new insights into efficient experiment design of RNA-seq studies.The code used in this paper is provided on: http://home.uchicago.edu/∼jiezhou/replication/. The expression data is deposited in the Gene Expression Omnibus under the accession ID GSE51403.
@article{Liu:2014:Bioinformatics:24319002,
abstract = {RNA-seq is replacing microarrays as the primary tool for gene expression studies. Many RNA-seq studies have used insufficient biological replicates, resulting in low statistical power and inefficient use of sequencing resources.We show the explicit trade-off between more biological replicates and deeper sequencing in increasing power to detect differentially expressed (DE) genes. In the human cell line MCF7, adding more sequencing depth after 10 M reads gives diminishing returns on power to detect DE genes, whereas adding biological replicates improves power significantly regardless of sequencing depth. We also propose a cost-effectiveness metric for guiding the design of large-scale RNA-seq DE studies. Our analysis showed that sequencing less reads and performing more biological replication is an effective strategy to increase power and accuracy in large-scale differential expression RNA-seq studies, and provided new insights into efficient experiment design of RNA-seq studies.The code used in this paper is provided on: http://home.uchicago.edu/∼jiezhou/replication/. The expression data is deposited in the Gene Expression Omnibus under the accession ID GSE51403.},
added-at = {2017-10-01T09:14:49.000+0200},
author = {Liu, Y and Zhou, J and White, K P},
biburl = {https://www.bibsonomy.org/bibtex/2a242cab70ae0558586709c2c9e6185e4/marcsaric},
description = {RNA-seq differential expression studies: more sequence or more replication? - PubMed - NCBI},
doi = {10.1093/bioinformatics/btt688},
interhash = {38e8d10f3f2b419f636032b99e381cb3},
intrahash = {a242cab70ae0558586709c2c9e6185e4},
journal = {Bioinformatics},
keywords = {experimental-design replicate rna-seq sequencing-depth statistics},
month = feb,
number = 3,
pages = {301-304},
pmid = {24319002},
timestamp = {2017-10-01T09:14:49.000+0200},
title = {RNA-seq differential expression studies: more sequence or more replication?},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24319002?dopt=Abstract},
volume = 30,
year = 2014
}