Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
出版年份 2018 全文链接
标题
Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
作者
关键词
-
出版物
NATURE BIOTECHNOLOGY
Volume 36, Issue 5, Pages 421-427
出版商
Springer Nature
发表日期
2018-04-02
DOI
10.1038/nbt.4091
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput
- (2017) Todd M Gierahn et al. NATURE METHODS
- Massively parallel digital transcriptional profiling of single cells
- (2017) Grace X. Y. Zheng et al. Nature Communications
- Batch effects and the effective design of single-cell gene expression studies
- (2017) Po-Yuan Tung et al. Scientific Reports
- A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation
- (2016) S. Nestorowa et al. BLOOD
- Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes
- (2016) Åsa Segerstolpe et al. Cell Metabolism
- De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data
- (2016) Dominic Grün et al. Cell Stem Cell
- Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes
- (2016) Nathan Lawlor et al. GENOME RESEARCH
- Resolving early mesoderm diversification through single-cell expression profiling
- (2016) Antonio Scialdone et al. NATURE
- A Single-Cell Transcriptome Atlas of the Human Pancreas
- (2016) Mauro J. Muraro et al. Cell Systems
- A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure
- (2016) Maayan Baron et al. Cell Systems
- Identification of cell types from single-cell transcriptomes using a novel clustering method
- (2015) Chen Xu et al. BIOINFORMATICS
- destiny: diffusion maps for large-scale single-cell data in R
- (2015) Philipp Angerer et al. BIOINFORMATICS
- Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells
- (2015) Allon M. Klein et al. CELL
- Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors
- (2015) Franziska Paul et al. CELL
- Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
- (2015) Evan Z. Macosko et al. CELL
- limma powers differential expression analyses for RNA-sequencing and microarray studies
- (2015) Matthew E. Ritchie et al. NUCLEIC ACIDS RESEARCH
- An interactive reference framework for modeling a dynamic immune system
- (2015) M. H. Spitzer et al. SCIENCE
- Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development
- (2014) Sean C. Bendall et al. CELL
- Normalization of RNA-seq data using factor analysis of control genes or samples
- (2014) Davide Risso et al. NATURE BIOTECHNOLOGY
- svaseq: removing batch effects and other unwanted noise from sequencing data
- (2014) Jeffrey T. Leek NUCLEIC ACIDS RESEARCH
- Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types
- (2014) D. A. Jaitin et al. SCIENCE
- featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
- (2013) Y. Liao et al. BIOINFORMATICS
- Accounting for technical noise in single-cell RNA-seq experiments
- (2013) Philip Brennecke et al. NATURE METHODS
- Smart-seq2 for sensitive full-length transcriptome profiling in single cells
- (2013) Simone Picelli et al. NATURE METHODS
- Quantifying Disorder through Conditional Entropy: An Application to Fluid Mixing
- (2013) Giovanni B. Brandani et al. PLoS One
- STAR: ultrafast universal RNA-seq aligner
- (2012) Alexander Dobin et al. BIOINFORMATICS
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started