Identifying sample mix-ups in eQTL data
Goals of this webinar:
Sample mix-ups interfere with our ability to detect genotype-phenotype associations. However, the presence of numerous eQTL with strong effects provides the opportunity to not just identify sample mix-ups, but also to correct them.
To illustrate methods for identifying sample duplicates and errors in sex annotations
To illustrate methods for identifying sample mix-ups in DNA and RNA samples from experimental cross data
Presented by:
Karl Broman, PhD
Professor
Department of Biostatistics and Medical Informatics
University of Wisconsin–Madison