Otari predicts tissue-specific isoform abundance changes caused by genetic variants using a graph-based attention model trained on genomic and long-read transcriptome data.

Cell Genomics · Jan 16, 2026Peer-reviewedBioinformatics

Comparative metagenomics using pan-metagenomics graphs

Izaak Coleman, Natalya Mametyarova, Andrey Zaznaev, Peiwen Cai, Lisa X Yu, Yoli Meydan, Aviya Litman, Ayushi Sharma, Lily He, Amanda Simkhovich, Dwayne Seeram, Heekuk Park, Yael R. Nobel, Aya Brown Kav, Itsik Pe’er, , Tal Korem

This paper introduces copangraph, a framework for comparative metagenomic analysis using sequence graphs, showing improved accuracy and computational efficiency in capturing genomic variation across microbial communities.

bioRxiv · Nov 24, 2025 · PreprintBioinformatics

Decomposition of phenotypic heterogeneity in autism reveals distinct and coherent genetic programs

Aviya Litman, Natalie Sauerwald, LeeAnne Green Snyder, Jennifer H. Foss‐Feig, Christopher Y. Park, Yun Hao, Ilan Dinstein, Chandra L. Theesfeld, Olga G. Troyanskaya

Mixture modeling of 239 phenotype features in 5,392 SPARK autistic children defines four replicable classes carrying distinct common and rare variant signatures and developmental gene-timing patterns.

Nature Genetics · Jul 1, 2025Peer-reviewedGenetic & Genomic Medicine✦ In-depth digest

Accurate and robust inference of microbial growth dynamics from metagenomic sequencing

Tyler Joseph, Philippe Chlenski, Aviya Litman, Tal Korem, Itsik Pe’er

The paper introduces CoPTR, a tool for computing peak-to-trough ratios from metagenomic data, showing it is more accurate and provides more estimates than existing methods, and demonstrates its application in a case-control study of irritable bowel disease.

Genome Research · Mar 1, 2022Peer-reviewedBioinformatics