Sriram Pendyala

The paper measures variant effects across the MAPK pathway in human cells, revealing how cell context influences variant function and identifying 14,412 previously unknown dominant negative variants.

Abundance scores for 8,891 TSC2 missense variants, plus mTOR pathway activity scores for 391, were calibrated to ACMG/AMP evidence. They putatively reclassify 212 of 276 clinical-cohort missense VUS.

The paper develops a high-throughput Visual Cell Sorting workflow to link nuclear compartment morphology to single-nucleus transcriptomes, identifying a conserved transcriptional signature of nucleolar size linked to proteostasis.

The paper introduces VIS-seq, an image-based method to assess variant effects on cellular phenotypes, revealing multidimensional variant impacts across different diseases.

STARCall processes in situ sequencing data by integrating image stitching, alignment, and read calling to improve genotype-to-phenotype mapping with reduced error and increased genotyped cells.

The paper develops a scalable workflow to reclassify variants of uncertain significance using experimental and predictive evidence, resolving 75% of VUS in 40 genes.

The paper develops iPSC-SGE to assess variant effects in diverse genetic and cell contexts, identifying pathogenic variants and essential disease genes.

The paper uses saturation genome editing to evaluate BARD1 variants, resolving most variants of uncertain significance and confirming their role in tumor suppression.

The paper analyzes variant classification disparities between European-like and non-European-like genetic ancestries and shows that MAVE data can reduce these disparities in VUS reclassification.

Pacybara improves the accuracy of long-read sequencing for barcoded mutagenized libraries by addressing sequencing errors and non-unique barcodes.

The paper introduces Sceptic, a supervised pseudotime analysis model that improves prediction accuracy over existing methods for scRNA-seq and single-nucleus image data.

This study uses hiPSC-derived cardiomyocytes to assess MYH7 variants' effects, showing pathogenic variants reduce protein abundance and cell survival.

CRaTER enriches for on-target gene-edited cells in hiPSCs, enabling efficient generation of variant libraries for studying cardiomyopathy-associated mutations.

This paper introduces a method to physically separate live cells based on visual phenotypes and uses it to study nuclear localization sequences and paclitaxel resistance in human cancers.