New York Genome Center

Exploring transcriptomic and genomic latent variable correction approaches in differential expression analysis

Abstract Background Differential expression analysis is a central tool for studying the biological processes altered in human diseases via transcriptomic signatures. However, transcriptomic datasets are systematically confounded by latent variables from two distinct sources: unme...

SUMO2 deletion changes chromatin accessibility and enhances cytotoxic T cell activation and tumor infiltration

Cytotoxic T cells [cytotoxic lymphocytes (CTLs)] are crucial for adaptive immunity leading to prolonged survival and potential cures for cancer. Recent clinical data have shown that pharmacological inhibition modifies the tumor microenvironment (TME) and activates CTLs, although...

RamanOmics decodes the spatial vibrational–molecular architecture of senescence in aging and repair

Aging and tissue repair involve heterogeneous remodeling across transcriptional, biochemical and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how these states co-evolve. Here we present RamanOmics, a multimodal framework integrat...

Sex-specific biological aging clocks across organs and omics

Sex differentially shapes aging, neurodevelopment and neurodegenerative diseases such as Alzheimer’s disease (AD). However, most biological aging clocks (artificial intelligence-predicted age minus chronological age) were trained on sex-pooled samples and implicitly assume sex in...

Accurately modeling RNase H-mediated antisense oligonucleotide efficacy.

, achieving a 5.72-fold reduction in screening effort compared to random selection. ASO Atlas provides the first systematic resource to rigorously evaluate hypotheses regarding key parameters in ASO design, including sequence composition, chemical modifications, and target region...

Omic risk scores are associated with COPD-related traits across three cohorts

Background: Chronic obstructive pulmonary disease (COPD) exhibits marked heterogeneity in lung function decline, mortality, exacerbations, and other disease-related outcomes. Omic risk scores (ORS) estimate the cumulative contribution of omics, such as the transcriptome, proteome...

Unsupervised discovery of functional sequence patterns from protein language model with MotifAE

Protein language models (pLMs) learn sequence patterns at evolutionary scale, but these patterns remain inaccessible within these “black box” models. To discover them, we developed MotifAE, an unsupervised framework based on the sparse autoencoder (SAE) architecture that projects...

Perplexity as a metric for isoform diversity in the human transcriptome

-an interpretable measure derived from entropy-that quantifies the effective number of isoforms per gene based on the full, unfiltered isoform ratio distribution. Calculating perplexity for 124 ENCODE4 PacBio LRS datasets spanning 55 human cell types, we show that it provides int...

Private information leakage from polygenic risk scores

Abstract Polygenic Risk Scores (PRSs) estimate the likelihood of individuals to develop complex diseases based on their genetic variations. While their use in clinical practice and direct-to-consumer genetic testing is growing, the privacy implications of publicly sharing PRS val...

A compendium of next-generation patient-derived models for diverse cancers

Abstract The development of new therapeutics and the validation of pathogenetic cancer mechanisms require representative laboratory models 1,2 . However, existing collections represent only a fraction of the diversity observed in human cancer 2–4 . Recent technologies have enable...