Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism

“Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism” by Jian Zhou, Christopher Park, Chandra Theesfeld, Yuan Yuan, Kirsty Sawicka, Jennifer Darnell, Claudia Scheckel, John Fak, Yoko Tajima, Robert Darnell, Olga Troyanskaya https://doi.org/10.1101/319681 It is well known that Autism has a strong genetic component. In recent years the discovery of genetic factors linked to Autism has skyrocketed, powered by next generation sequencing. Exome sequencing studies have allowed the discovery of hundreds of coding genetic risk variants. »

Human 5' UTR design and variant effect prediction from a massively parallel translation assay

“Human 5’ UTR design and variant effect prediction from a massively parallel translation assay” by Paul J. Sample, Ban Wang, David W. Reid, Vlad Presnyak, Iain McFadyen, David R. Morris, and Georg Seelig. https://doi.org/10.1101/310375 I selected this article for review for two reasons: I am excited to learn about applications of massively parallel reporter assays (MPRAs). I have a general interest in methods that use deep learning (in this case convolutional neural networks) with genomic data. »