Bioinformatics Data Analysis Pipeline- Single Cell RNA-Seq

A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation and Feature Barcode analysis from single cell data.

Reference: PMID: 28091601

Contact: Qin Ma

Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. Seurat aims to enable users to identify and interpret sources of heterogeneity from single-cell transcriptomic measurements and to integrate diverse types of single-cell data.

Reference: PMID: 37231261

Contact: Qin Ma

An unsupervised algorithm to infer transcriptome dynamics of a temporal process such as cell differentiation using single-cell RNA-Seq data.

Reference: PMID: 24658644

Contact: Qin Ma

A method for inferring cell lineages and pseudotimes from single-cell gene expression data.

Reference: PMID: 29914354

Contact: Qin Ma

A computational framework for the annotation of scRNA-seq by reference to bulk transcriptomes.

Reference: PMID: 30643263

Contact: Qin Ma

A fully-automated and ultra-fast cell-type identification based solely on a given scRNA-seq data, along with a comprehensive cell marker database as background information.

Reference: PMID: 35273156

Contact: Qin Ma

A web application that uses an annotated reference dataset to automate the processing, analysis and interpretation of a new single-cell RNA-seq or ATAC-seq experiment.

Reference: PMID: 31178118

Contact: Qin Ma

A scalable toolkit for analyzing single-cell gene expression data.  It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing.

Reference: PMID: 29409532

Contact: Qin Ma

An algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions.

Reference: PMID: 31740819

Contact: Qin Ma

A method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts.

Reference: PMID: 29961576

Contact: Qin Ma

A tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data

Reference: PMID: 33597522

Contact: Qin Ma

A web server for active regulons within a specific cell type, i.e., cell-type-specific regulons (CTSR), inference from scRNA-Seq data for human and mouse

Reference: PMID: 32421805

Contact: Qin Ma

scGNN (single-cell graph neural network) can provide a hypothesis-free deep learning framework for scRNA-Seq analyses. scGNN provides an effective representation of gene expression and cell–cell relationships. It is also a powerful framework that can be applied to general scRNA-Seq analyses.

Reference: PMID: 33767197

Contact: Qin Ma