netNMF-sc: leveraging gene–gene interactions for imputation and dimensionality reduction in single-cell expression analysis

Droplet scRNA-seq is not zero-inflated

(2020) Valentine Svensson   NATURE BIOTECHNOLOGY

Probabilistic Count Matrix Factorization for Single Cell Expression Data Analysis

(2019) G Durif et al.   BIOINFORMATICS

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data

(2019) Shiquan Sun et al.   BMC Systems Biology

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama

(2019) Brian Hie et al.   NATURE BIOTECHNOLOGY

A unified statistical framework for single cell and bulk RNA sequencing data

(2018) Lingxue Zhu et al.   Annals of Applied Statistics

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion

(2018) David van Dijk et al.   CELL

bigSCale: an analytical framework for big-scale single-cell data

(2018) Giovanni Iacono et al.   GENOME RESEARCH

SAVER: gene expression recovery for single-cell RNA sequencing

(2018) Mo Huang et al.   NATURE METHODS

An accurate and robust imputation method scImpute for single-cell RNA-seq data

(2018) Wei Vivian Li et al.   Nature Communications

Brain Cell Type Specific Gene Expression and Co-expression Network Architectures

(2018) Andrew T. McKenzie et al.   Scientific Reports

Comparative Analysis of Single-Cell RNA Sequencing Methods

(2017) Christoph Ziegenhain et al.   MOLECULAR CELL

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

(2017) Bo Wang et al.   NATURE METHODS

Using neural networks for reducing the dimensions of single-cell RNA-Seq data

(2017) Chieh Lin et al.   NUCLEIC ACIDS RESEARCH

Massively parallel digital transcriptional profiling of single cells

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

Cellular and Molecular Characterization of Microglia: A Unique Immune Cell Population

(2017) Carole Sousa et al.   Frontiers in Immunology

A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer

(2016) Daniel Dominguez et al.   CELL RESEARCH

Single-cell barcoding and sequencing using droplet microfluidics

(2016) Rapolas Zilionis et al.   Nature Protocols

COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH)

(2016) Sunmo Yang et al.   NUCLEIC ACIDS RESEARCH

Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells

(2015) Allon M. Klein et al.   CELL

Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

(2015) Jacob H. Levine et al.   CELL

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

(2015) Evan Z. Macosko et al.   CELL

Next generation transcriptomics and genomics elucidate biological complexity of microglia in health and disease

(2015) Paul D. Wes et al.   GLIA

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

(2015) Florian Buettner et al.   NATURE BIOTECHNOLOGY

Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

(2015) A. Zeisel et al.   SCIENCE

COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems

(2014) Yasunobu Okamura et al.   NUCLEIC ACIDS RESEARCH

Construction and Validation of a Regulatory Network for Pluripotency and Self-Renewal of Mouse Embryonic Stem Cells

(2014) Huilei Xu et al.   PLoS Computational Biology

Network-based stratification of tumor mutations

(2013) Matan Hofree et al.   NATURE METHODS

A human functional protein interaction network and its application to cancer data analysis

(2010) Guanming Wu et al.   GENOME BIOLOGY

GeneSigDB—a curated database of gene expression signatures

(2009) Aedín C. Culhane et al.   NUCLEIC ACIDS RESEARCH

RNA-Seq: a revolutionary tool for transcriptomics

(2008) Zhong Wang et al.   NATURE REVIEWS GENETICS