Ryan Poplin
YOU?
Author Swipe
View article: Challenges of Accuracy in Germline Clinical Sequencing Data
Challenges of Accuracy in Germline Clinical Sequencing Data Open
This Genomics and Precision Health article explains how genetic testing has evolved from detection of prespecified and unknown variants to assessing entire genomes to establish diagnoses using high-throughput sequencing.
View article: SyntheticFur dataset for neural rendering
SyntheticFur dataset for neural rendering Open
We introduce a new dataset called SyntheticFur built specifically for machine learning training. The dataset consists of ray traced synthetic fur renders with corresponding rasterized input buffers and simulation data files. We procedurall…
View article: Analysis of protein-coding genetic variation in 60,706 humans
Analysis of protein-coding genetic variation in 60,706 humans Open
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence …
View article: Identifying viruses from metagenomic data using deep learning
Identifying viruses from metagenomic data using deep learning Open
Background The recent development of metagenomic sequencing makes it possible to massively sequence microbial genomes including viral genomes without the need for laboratory culture. Existing reference‐based and gene homology‐based methods…
View article: Likelihood Ratios for Out-of-Distribution Detection
Likelihood Ratios for Out-of-Distribution Detection Open
Discriminative neural networks offer little or no performance guarantees when deployed on data not generated by the same process as the training distribution. On such out-of-distribution (OOD) inputs, the prediction may not only be erroneo…
View article: GenomeWarp: an alignment-based variant coordinate transformation
GenomeWarp: an alignment-based variant coordinate transformation Open
Summary Reference genomes are refined to reflect error corrections and other improvements. While this process improves novel data generation and analysis, incorporating data analyzed on an older reference genome assembly requires transform…
View article: CrowdVariant: a crowdsourcing approach to classify copy number variants
CrowdVariant: a crowdsourcing approach to classify copy number variants Open
Copy number variants (CNVs) are an important type of genetic variation that play a causal role in many diseases. The ability to identify high quality CNVs is of substantial clinical relevance. However, CNVs are notoriously difficult to ide…
View article: A deep learning approach to pattern recognition for short DNA sequences
A deep learning approach to pattern recognition for short DNA sequences Open
Motivation Inferring properties of biological sequences--such as determining the species-of-origin of a DNA sequence or the function of an amino-acid sequence--is a core task in many bioinformatics applications. These tasks are often solve…
View article: Scaling accurate genetic variant discovery to tens of thousands of samples
Scaling accurate genetic variant discovery to tens of thousands of samples Open
Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel ass…
View article: Learning to Count Mosquitoes for the Sterile Insect Technique
Learning to Count Mosquitoes for the Sterile Insect Technique Open
Mosquito-borne illnesses such as dengue, chikungunya, and Zika are major global health problems, which are not yet addressable with vaccines and must be countered by reducing mosquito populations. The Sterile Insect Technique (SIT) is a pr…
View article: A Low-Frequency Inactivating <i>AKT2</i> Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk
A Low-Frequency Inactivating <i>AKT2</i> Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk Open
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 3…
View article: A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk
A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk Open
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 3…
View article: Creating a universal SNP and small indel variant caller with deep neural networks
Creating a universal SNP and small indel variant caller with deep neural networks Open
Next-generation sequencing (NGS) is a rapidly evolving set of technologies that can be used to determine the sequence of an individual’s genome 1 by calling genetic variants present in an individual using billions of short, errorful sequen…
View article: CrowdVariant: a crowdsourcing approach to classify copy number variants
CrowdVariant: a crowdsourcing approach to classify copy number variants Open
Copy number variants (CNVs) are an important type of genetic variation and play a causal role in many diseases. However, they are also notoriously difficult to identify accurately from next-generation sequencing (NGS) data. For larger CNVs…