Sivan Leviyang

A Metacell Model of Single Cell RNA-seq Counts Yields a Gaussian Mixture Model in PCA Space

The paper shows that applying a metacell model to scRNA-seq data results in PCA embeddings that follow a Gaussian mixture model, but underestimates variance in real datasets due to unaccounted gene correlations.

Resolution Tradeoffs in Modularity Clustering with Application to Single Cell RNA-seq

This paper analyzes resolution tradeoffs in modularity clustering for scRNA-seq, showing how splitting resolution relates to subgraph frequency and providing error tradeoff examples.

A Random Matrix Approach to Single Cell RNA-seq Analysis

This paper introduces a random matrix framework to quantify transcriptional signals in scRNA-seq and assess their impact on cell clustering resolution.

Tree Based Co-Clustering Identifies Variation in Chromatin Accessibility Across Hematopoietic Cell Types

The paper uses a co-clustering approach to identify chromatin accessibility variation across hematopoietic cell types, capturing 80% of variation with 12 cell type clusters and 20 genomic locus clusters.