This repository contains a Python implementation of the ENHANCE algorithm for denoising single-cell RNA-Seq data (Wagner et al., 2019). The R implementation can be found in a separate repository.

To understand the importance of eIF4F components, we employed computational methods on large public datasets to investigate the impact of positive selection on eIF4F dysregulation in cancer. By ...

scAI is an unsupervised approach for integrative analysis of gene expression and chromatin accessibility or DNA methylation proflies measured in the same individual cells. scAI infers a set of ...

Reduced-dimension or spatial in situ scatter plots are widely employed in bioinformatics papers analyzing single-cell data to present phenomena or cell-conditions of interest in cell groups. When ...

Single-cell RNA sequencing (scRNA-Seq) enables researchers to quantify the transcriptomes of individual cells. The capacity of researchers to perform this type of analysis has allowed researchers to ...

Topic modeling is an unsupervised machine learning technique that automatically identifies different topics present in a document (textual data). Data has become a key asset/tool to run many ...

It is well recognized that batch effect in single-cell RNA sequencing (scRNA-seq) data remains a big challenge when integrating different datasets. Here, we proposed deepMNN, a novel deep ...

Tumor heterogeneity is widely attributed to the imperfection of DNA replication. However, little is known about the mechanoregulation of tumor heterogeneity. Here, we report that volumetric ...