The Doppelganger Effect: Hidden Duplicates in Databases of Transcriptome Profiles.

ABSTRACT: Whole-genome analysis of cancer specimens is commonplace, and investigators frequently share or re-use specimens in later studies. Duplicate expression profiles in public databases will impact re-analysis if left undetected, a so-called "doppelgänger" effect. We propose a method that should be routine practice to accurately match duplicate cancer transcriptomes when nucleotide-level sequence data are unavailable, even for samples profiled by different microarray technologies or by both microarray and RNA sequencing. We demonstrate the effectiveness of the method in databases containing dozens of datasets and thousands of ovarian, breast, bladder, and colorectal cancer microarray profiles and of matching microarray and RNA sequencing expression profiles from The Cancer Genome Atlas (TCGA).

SUBMITTER: Waldron L 

PROVIDER: S-EPMC5241903 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature