November 2019: Elkon: Technical bias in RNA sequencing

A new study by Dr. Ran Elkon, Edmond J. Safra faculty fellow (Medicine) and colleagues, identifies a frequent technical bias in RNA-seq data. 

Reproducibility is a major challenge in experimental biology, and with the increasing complexity of data generated by genomic-scale techniques this concern is immensely amplified. RNA-seq, one of the most widely used methods in modern molecular biology, allows in a single test the simultaneous measurement of the expression level of all the genes in a given sample. The study identified a frequent technical bias in RNA-seq data, which often leads to false findings. Importantly, the study also shows how this bias can be corrected. Read an interview with Dr. Elkon on these findings in The Scientist journal.