RLE plots: Visualizing unwanted variation in high dimensional data
AuthorGandolfo, LC; Speed, TP
Source TitlePLoS One
PublisherPUBLIC LIBRARY SCIENCE
AffiliationSchool of Mathematics and Statistics
Medical Biology (W.E.H.I.)
Document TypeJournal Article
CitationsGandolfo, L. C. & Speed, T. P. (2018). RLE plots: Visualizing unwanted variation in high dimensional data. PLOS ONE, 13 (2), https://doi.org/10.1371/journal.pone.0191629.
Access StatusOpen Access
Unwanted variation can be highly problematic and so its detection is often crucial. Relative log expression (RLE) plots are a powerful tool for visualizing such variation in high dimensional data. We provide a detailed examination of these plots, with the aid of examples and simulation, explaining what they are and what they can reveal. RLE plots are particularly useful for assessing whether a procedure aimed at removing unwanted variation, i.e. a normalization procedure, has been successful. These plots, while originally devised for gene expression data from microarrays, can also be used to reveal unwanted variation in many other kinds of high dimensional data, where such variation can be problematic.
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