-
Article
Open AccessUnsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction
Although high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, ...
-
Chapter and Conference Paper
Multimodal LLMs for Health Grounded in Individual-Specific Data
Foundation large language models (LLMs) have shown an impressive ability to solve tasks across a wide range of fields including health. To effectively solve personalized health tasks, LLMs need the ability to ...
-
Article
Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a qu...
-
Article
DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer
Circular consensus sequencing with Pacific Biosciences (PacBio) technology generates long (10–25 kilobases), accurate ‘HiFi’ reads by combining serial observations of a DNA molecule into a consensus sequence. ...
-
Article
Open AccessDeepNull models non-linear covariate effects to improve phenotypic prediction and association power
Genome-wide association studies (GWASs) examine the association between genotype and phenotype while adjusting for a set of covariates. Although the covariates may have non-linear or interactive effects, due t...
-
Article
Open AccessA population-specific reference panel for improved genotype imputation in African Americans
There is currently a dearth of accessible whole genome sequencing (WGS) data for individuals residing in the Americas with Sub-Saharan African ancestry. We generated whole genome sequencing data at intermediat...
-
Article
An open resource for accurately benchmarking small variant and reference calls
Benchmark small variant calls are required for develo**, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply...
-
Article
A universal SNP and small-indel variant caller using deep neural networks
DeepVariant uses convolutional neural networks to improve the accuracy of variant calling.
-
Article
Human-specific loss of regulatory DNA and the evolution of human-specific traits
A computational survey of the human genome has identified more than 500 human-specific genomic deletions that remove sequences that are highly conserved between chimpanzees and other animals. These are genomic...
-
Article
GREAT improves functional interpretation of cis-regulatory regions
ChIP-Seq data are usually analyzed with approaches developed for microarrays, which only consider binding events within a few kilobases of a gene. McLean et al. present an algorithm that takes into account more d...
