Marzieh Haghighi

A scalable approach to resolving variants of uncertain significance

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

Identifying and targeting abnormal mitochondrial localization associated with psychosis

The paper identifies a mitochondrial localization phenotype in psychosis patients and uses a cell-based assay to screen for compounds and genes affecting this phenotype.

Morphological map of under- and over-expression of genes in human cells

The paper presents a comprehensive genetic perturbation dataset using Cell Painting to analyze gene expression effects in human cells, revealing novel gene clusters and functional relationships.

A genome-wide atlas of human cell morphology

The paper presents a genome-wide perturbation atlas using CRISPR-Cas9 knockouts to link genes to cellular phenotypes, identifying TMEM251/LYSET as a Golgi-resident protein involved in lysosomal enzyme trafficking.

An artificial intelligence-based model for prediction of Clonal Hematopoiesis mutants in cell-free DNA samples

The paper presents a machine learning framework to classify variants in cell-free DNA as clonal hematopoiesis or tumor origin, achieving better classification rates than existing methods.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

The paper introduces a dataset of cell morphology images treated with matched chemical and genetic perturbations and evaluates methods for identifying perturbation similarities.

High-dimensional phenotyping to define the genetic basis of cellular morphology

This study identifies genetic variants associated with cellular morphology using high-content imaging and genomic data from iPSCs.

High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations

The paper provides four datasets combining gene expression and morphology profiles from over 28,000 genetic and chemical perturbations for multi-modal analysis.

Morphology and gene expression profiling provide complementary information for mapping cell state

The paper compares morphology and gene expression data to determine their complementary roles in mapping cell states across drug perturbations.