Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters

Challenges in unsupervised clustering of single-cell RNA-seq data

(2019) Vladimir Yu Kiselev et al.   NATURE REVIEWS GENETICS

Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data

(2019) George C. Linderman et al.   NATURE METHODS

DrImpute: imputing dropout events in single cell RNA sequencing data

(2018) Wuming Gong et al.   BMC BIOINFORMATICS

Identifying cell populations with scRNASeq

(2018) Tallulah S. Andrews et al.   MOLECULAR ASPECTS OF MEDICINE

dropClust: efficient clustering of ultra-large scRNA-seq data

(2018) Debajyoti Sinha et al.   NUCLEIC ACIDS RESEARCH

OUP accepted manuscript

(2018)   NUCLEIC ACIDS RESEARCH

Massively parallel digital transcriptional profiling of single cells

(2017) Grace X. Y. Zheng et al.   Nature Communications

The Human Cell Atlas

(2017) Aviv Regev et al.   eLife

Revealing the vectors of cellular identity with single-cell genomics

(2016) Allon Wagner et al.   NATURE BIOTECHNOLOGY

Robust enumeration of cell subsets from tissue expression profiles

(2015) Aaron M Newman et al.   NATURE METHODS

MMAD: microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples

(2013) David A. Liebner et al.   BIOINFORMATICS

Digital sorting of complex tissues for cell type-specific gene expression profiles

(2013) Yi Zhong et al.   BMC BIOINFORMATICS

Computational deconvolution: extracting cell type-specific information from heterogeneous samples

(2013) Shai S Shen-Orr et al.   CURRENT OPINION IN IMMUNOLOGY

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

(2013) El-ad David Amir et al.   NATURE BIOTECHNOLOGY

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

(2013) Neta S. Zuckerman et al.   PLoS Computational Biology

PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

(2012) Wenlian Qiao et al.   PLoS Computational Biology

Optimal Deconvolution of Transcriptional Profiling Data Using Quadratic Programming with Application to Complex Clinical Blood Samples

(2011) Ting Gong et al.   PLoS One

Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus

(2009) Alexander R. Abbas et al.   PLoS One