Ramyar Molania

ClustoCell reveals cell states and their markers from single-cell transcriptomes

ClustoCell identifies cell states and markers from single-cell transcriptomes by analyzing transcriptional architecture, improving accuracy and stability over existing methods.

Fast, accurate and scalable normalization for RNA sequencing data with the RUVprps software package

The paper introduces RUVprps, a software package for normalizing RNA-seq data by removing unwanted variation, offering improved performance and features for analysis.

Removing unwanted variation from large-scale cancer RNA-sequencing data

This paper identifies major sources of unwanted variation in cancer RNA-seq data and proposes a novel method to remove them using pseudo-replicates of pseudo-samples.

RUV-III-NB: Normalization of single cell RNA-seq Data

RUV-III-NB normalizes scRNA-seq data by removing unwanted variation from both cell embeddings and gene-level counts, improving differential expression and clustering results across multiple datasets.

A new normalization for the Nanostring nCounter gene expression assay

The paper introduces a new normalization method, RUV-III, for Nanostring nCounter gene expression data and evaluates its effectiveness across multiple datasets.

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

GRIDSS detects genomic rearrangements with high sensitivity and specificity using a positional de Bruijn graph assembler, outperforming existing methods on simulated and tumor data.