Month: January 2017


[PMID:28092658] [Nature Biotechnology]

Mutation effects predicted from sequence co-variation

“Most prediction methods exploit evolutionary sequence conservation but do not consider the interdependencies of residues or bases. We present EVmutation, an unsupervised statistical method for predicting the effects of mutations that explicitly captures residue dependencies between positions.”


Deep Neural Networks as A Dermatologist

[PMID:28117445] [Nature]

Dermatologist-level classification of skin cancer with deep neural networks

“classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images””test its performance against 21 board-certified dermatologists”

Somatic Mutation Process Duplicates Germline Loci

[PMID:28112740] [Nature Genetics]
A somatic-mutational process recurrently duplicates germline susceptibility loci and tissue-specific super-enhancers in breast cancers

“a somatic-rearrangement mutational process affecting coding sequences and noncoding regulatory elements and contributing a continuum of driver consequences, from modest to strong effects, thereby supporting a polygenic model of cancer development.” Work from Peter Campbell, Michael Stratton & Serena Nik-Zainab.


[PMID:28093075] [Genome Biology]

GAVIN: Gene-Aware Variant INterpretation for medical sequencing

“a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%.”

Purifying Selection in Cancer

[PMID:28027311] [PLoS Genetics]

Somatic Mutation Patterns in Hemizygous Genomic Regions Unveil Purifying Selection during Tumor Evolution

“cancer cells additionally depend on a large number of genes involved in basic cellular processes. While such genes should in theory be subject to strong purifying (negative) selection against damaging somatic mutations, these patterns have been elusive and purifying selection remains inadequately explored in cancer. Here, we hypothesized that purifying selection should be evident in hemizygous genomic regions, where damaging mutations cannot be compensated for by healthy alleles.”