Biology subjects

Paggi, J. M.

Publications and source records attributed to Paggi, J. M..

3 recordsLinked to original sources

bioRxiv2018

S-CAP extends clinical-grade pathogenicity prediction to genetic variants that affect RNA splicing

There are over 15,000 known variants that cause human inherited disease by disrupting RNA splicing. While several in silico methods such as CADD, EIGEN and LINSIGHT are commonly used to predict the pathogenicity of noncoding variants, we introduce S-CAP, a tool developed specially for splicing which is better able to effectively distinguish pathogenic splicing-relevant variants from benign variants. S-CAP is a novel splicing pathogenicity predictor that reduces the number of splicing-relevant variants of uncertain significance in patient exomes by 41%, a nearly 3-fold improvement over existing noncoding pathogenicity measures while correctly classifying known pathogenic splicing-relevant variants with a clinical-grade 95% sensitivity.

genomics↗

bioRxiv2018

HISAT-genotype: Next Generation Genomic Analysis Platform on a Personal Computer

Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses of human genomes. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT-genotype, for representing and searching an expanded model of the human reference genome, in which a comprehensive catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a very fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate HISAT-genotypes accuracy for HLA typing, a critical task in human organ transplantation, and for the DNA fingerprinting tests widely used in forensics. In both applications, HISAT-genotype not only improves upon earlier computational methods, but matches or exceeds the accuracy of laboratory-based assays.\n\nOne Sentence SummaryHISAT-genotype is a software platform that has the ability to genotype all the genes in an individuals genome within a few hours on a desktop computer.

bioinformatics↗

bioRxiv2017

A sequence-based, deep learning model accurately predicts RNA splicing branchpoints

Experimental detection of RNA splicing branchpoints, the nucleotide serving as the nucleophile in the first catalytic step of splicing, is difficult. To date, annotations exist for only 16-21% of 3 splice sites in the human genome and even these limited annotations have been shown to be plagued by noise. We develop a sequence-only, deep learning based branchpoint predictor, LaBranchoR, which we conclude predicts a correct branchpoint for over 90% of 3 splice sites genome-wide. Our predicted branchpoints show large agreement with trends observed in the raw data, but analysis of conservation signatures and overlap with pathogenic variants reveal that our predicted branchpoints are generally more reliable than the raw data itself. We use our predicted branchpoints to identify a sequence element upstream of branchpoints consistent with extended U2 snRNA base pairing, show an association between weak branchpoints and alternative splicing, and explore the effects of variants on branchpoints.

bioinformatics↗