Bias, robustness and scalability in single-cell differential expression analysis

Single-cell mRNA quantification and differential analysis with Census

(2017) Xiaojie Qiu et al.   NATURE METHODS

Salmon provides fast and bias-aware quantification of transcript expression

(2017) Rob Patro et al.   NATURE METHODS

Massively parallel digital transcriptional profiling of single cells

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

Beta-Poisson model for single-cell RNA-seq data analyses

(2016) Trung Nghia Vu et al.   BIOINFORMATICS

MultiQC: summarize analysis results for multiple tools and samples in a single report

(2016) Philip Ewels et al.   BIOINFORMATICS

Discrete distributional differential expression (D3E) - a tool for gene expression analysis of single-cell RNA-seq data

(2016) Mihails Delmans et al.   BMC BIOINFORMATICS

iCOBRA: open, reproducible, standardized and live method benchmarking

(2016) Charlotte Soneson et al.   NATURE METHODS

Data-driven hypothesis weighting increases detection power in genome-scale multiple testing

(2016) Nikolaos Ignatiadis et al.   NATURE METHODS

The Ensembl gene annotation system

(2016) Bronwen L. Aken et al.   Database-The Journal of Biological Databases and Curation

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

(2015) Allon M. Klein et al.   CELL

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

(2015) Evan Z. Macosko et al.   CELL

Spatial reconstruction of single-cell gene expression data

(2015) Rahul Satija et al.   NATURE BIOTECHNOLOGY

Orchestrating high-throughput genomic analysis with Bioconductor

(2015) Wolfgang Huber et al.   NATURE METHODS

ROTS: reproducible RNA-seq biomarker detector—prognostic markers for clear cell renal cell cancer

(2015) Fatemeh Seyednasrollah et al.   NUCLEIC ACIDS RESEARCH

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

(2014) Cole Trapnell et al.   NATURE BIOTECHNOLOGY

Bayesian approach to single-cell differential expression analysis

(2014) Peter V Kharchenko et al.   NATURE METHODS

Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing

(2014) Dmitry Usoskin et al.   NATURE NEUROSCIENCE

Robustly detecting differential expression in RNA sequencing data using observation weights

(2014) Xiaobei Zhou et al.   NUCLEIC ACIDS RESEARCH

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

(2014) Charity W Law et al.   GENOME BIOLOGY

Transcriptome and genome sequencing uncovers functional variation in humans

(2013) Tuuli Lappalainen et al.   NATURE

Differential abundance analysis for microbial marker-gene surveys

(2013) Joseph N Paulson et al.   NATURE METHODS

Smart-seq2 for sensitive full-length transcriptome profiling in single cells

(2013) Simone Picelli et al.   NATURE METHODS

Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments

(2012) Andrew McDavid et al.   BIOINFORMATICS

Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

(2012) Davis J. McCarthy et al.   NUCLEIC ACIDS RESEARCH

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

(2011) Jun Li et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Independent filtering increases detection power for high-throughput experiments

(2010) R. Bourgon et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A scaling normalization method for differential expression analysis of RNA-seq data

(2010) Mark D Robinson et al.   GENOME BIOLOGY

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

(2009) M. D. Robinson et al.   BIOINFORMATICS

mRNA-Seq whole-transcriptome analysis of a single cell

(2009) Fuchou Tang et al.   NATURE METHODS

Reproducibility-Optimized Test Statistic for Ranking Genes in Microarray Studies

(2008) L.L. Elo et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics