Related references
Note: Only part of the references are listed.Single-cell mRNA quantification and differential analysis with Census
Xiaojie Qiu et al.
NATURE METHODS (2017)
Salmon provides fast and bias-aware quantification of transcript expression
Rob Patro et al.
NATURE METHODS (2017)
Massively parallel digital transcriptional profiling of single cells
Grace X. Y. Zheng et al.
NATURE COMMUNICATIONS (2017)
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data
Aaron T. L. Lun et al.
BIOSTATISTICS (2017)
ROTS: reproducible RNA-seq biomarker detector-prognostic markers for clear cell renal cell cancer
Fatemeh Seyednasrollah et al.
NUCLEIC ACIDS RESEARCH (2016)
Beta-Poisson model for single-cell RNA-seq data analyses
Trung Nghia Vu et al.
BIOINFORMATICS (2016)
MultiQC: summarize analysis results for multiple tools and samples in a single report
Philip Ewels et al.
BIOINFORMATICS (2016)
Discrete distributional differential expression (D3E) - a tool for gene expression analysis of single-cell RNA-seq data
Mihails Delmans et al.
BMC BIOINFORMATICS (2016)
iCOBRA: open, reproducible, standardized and live method benchmarking
Charlotte Soneson et al.
NATURE METHODS (2016)
Data-driven hypothesis weighting increases detection power in genome-scale multiple testing
Nikolaos Ignatiadis et al.
NATURE METHODS (2016)
The Ensembl gene annotation system
Bronwen L. Aken et al.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION (2016)
Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
Aaron T. L. Lun et al.
GENOME BIOLOGY (2016)
Beyond comparisons of means: understanding changes in gene expression at the single-cell level
Catalina A. Vallejos et al.
GENOME BIOLOGY (2016)
A statistical approach for identifying differential distributions in single-cell RNA-seq experiments
Keegan D. Korthauer et al.
GENOME BIOLOGY (2016)
Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells
Allon M. Klein et al.
CELL (2015)
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Evan Z. Macosko et al.
CELL (2015)
Spatial reconstruction of single-cell gene expression data
Rahul Satija et al.
NATURE BIOTECHNOLOGY (2015)
Orchestrating high-throughput genomic analysis with Bioconductor
Wolfgang Huber et al.
NATURE METHODS (2015)
Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing
Dmitry Usoskin et al.
NATURE NEUROSCIENCE (2015)
MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data
Greg Finak et al.
GENOME BIOLOGY (2015)
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Cole Trapnell et al.
NATURE BIOTECHNOLOGY (2014)
Bayesian approach to single-cell differential expression analysis
Peter V. Kharchenko et al.
NATURE METHODS (2014)
Robustly detecting differential expression in RNA sequencing data using observation weights
Xiaobei Zhou et al.
NUCLEIC ACIDS RESEARCH (2014)
voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Charity W. Law et al.
GENOME BIOLOGY (2014)
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Michael I. Love et al.
GENOME BIOLOGY (2014)
Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments
Andrew McDavid et al.
BIOINFORMATICS (2013)
Transcriptome and genome sequencing uncovers functional variation in humans
Tuuli Lappalainen et al.
NATURE (2013)
Differential abundance analysis for microbial marker-gene surveys
Joseph N. Paulson et al.
NATURE METHODS (2013)
Smart-seq2 for sensitive full-length transcriptome profiling in single cells
Simone Picelli et al.
NATURE METHODS (2013)
Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data
Jun Li et al.
STATISTICAL METHODS IN MEDICAL RESEARCH (2013)
Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
Davis J. McCarthy et al.
NUCLEIC ACIDS RESEARCH (2012)
edgeR: a Bioconductor package for differential expression analysis of digital gene expression data
Mark D. Robinson et al.
BIOINFORMATICS (2010)
Independent filtering increases detection power for high-throughput experiments
Richard Bourgon et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
A scaling normalization method for differential expression analysis of RNA-seq data
Mark D. Robinson et al.
GENOME BIOLOGY (2010)
mRNA-Seq whole-transcriptome analysis of a single cell
Fuchou Tang et al.
NATURE METHODS (2009)
Reproducibility-optimized test statistic for ranking genes in microarray studies
Laura L. Elo et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2008)
Multiple-laboratory comparison of microarray platforms
RA Irizarry et al.
NATURE METHODS (2005)
Share Paper
