Analysis and Correction of Inappropriate Image Duplication: The Molecular and Cellular Biology Experience

“Analysis and Correction of Inappropriate Image Duplication: The Molecular and Cellular Biology Experience” by Arturo Casadevall, Elisabeth M Bik, Ferric C Fang, Amy Kullas, Roger J Davis. https://doi.org/10.1101/354621 [Ed note: we’re using the bioRxiv listing information because that’s what we sent for review, but the author order has changed on the published paper and on that Dr. Bik is first author.] I selected this article for review for a few reasons: »

Mapping DNA sequence to transcription factor binding energy in vivo

“Mapping DNA sequence to transcription factor binding energy in vivo” by Stephanie L Barnes, Nathan M Belliveau, William T Ireland, Justin B Kinney and Robert Phillips https://doi.org/10.1101/331124 In this article, Barnes and colleagues constructed a libraries of strains in which GFP expression is controlled by a transcription factor, and the transcription factor (TF) binding sites were randomly mutated. Libraries were sorted by GFP fluorescence and sequenced to determine the likelihood that a given binding site corresponds to a range of fluroescence. »

Single cell RNA-seq denoising using a deep count autoencoder

“Single cell RNA-seq denoising using a deep count autoencode” by Gokcen Eraslan, Lukas M. Simon (both first-authors contributed equally), Maria Mircea, Nikola S. Mueller, Fabian J. Theis. https://doi.org/10.1101/300681 I selected this article for review for two reasons: I work with single-cell RNA-Sequencing (scRNA-seq) data quite a bit and I have a general interest in methods that remove technical sources of variation from it. I have a general interest in methods that use machine learning approaches (in this case an autoencoder network) with genomic data. »

The harmonic mean p-value for combining dependent tests

“The harmonic mean p-value for combining dependent tests” by Daniel J. Wilson. https://doi.org/10.1101/171751 I selected this article for review for the following reasons: Multiple testing approaches are extraordinarily important in modern science and I am personally interested in new developments in that area. The mathematical solution and the equivalency between the mean maximized likelihood and the harmonic mean p-values (HMP) seemed particularly elegant. Genome-wide association studies are well-known for their dependent testing issues, so an application to this area of this kind of approach seemed particularly interesting. »

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. »