ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq
Andrew D Fernandes,
Jean M Macklaim,
Thomas G Linn,
Gregor Reid and
Gregory B Gloor
PLOS ONE, 2013, vol. 8, issue 7, 1-15
Abstract:
Experimental variance is a major challenge when dealing with high-throughput sequencing data. This variance has several sources: sampling replication, technical replication, variability within biological conditions, and variability between biological conditions. The high per-sample cost of RNA-Seq often precludes the large number of experiments needed to partition observed variance into these categories as per standard ANOVA models. We show that the partitioning of within-condition to between-condition variation cannot reasonably be ignored, whether in single-organism RNA-Seq or in Meta-RNA-Seq experiments, and further find that commonly-used RNA-Seq analysis tools, as described in the literature, do not enforce the constraint that the sum of relative expression levels must be one, and thus report expression levels that are systematically distorted. These two factors lead to misleading inferences if not properly accommodated. As it is usually only the biological between-condition and within-condition differences that are of interest, we developed ALDEx, an ANOVA-like differential expression procedure, to identify genes with greater between- to within-condition differences. We show that the presence of differential expression and the magnitude of these comparative differences can be reasonably estimated with even very small sample sizes.
Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0067019 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 67019&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0067019
DOI: 10.1371/journal.pone.0067019
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().