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Title
Computational approaches for interpreting scRNA-seq data
Authors
Keywords
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Journal
FEBS LETTERS
Volume 591, Issue 15, Pages 2213-2225
Publisher
Wiley
Online
2017-05-19
DOI
10.1002/1873-3468.12684
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- (2017) Valentine Svensson et al. NATURE METHODS
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- (2016) Christof Angermueller et al. NATURE METHODS
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- (2016) Ross Cloney NATURE REVIEWS GENETICS
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- (2016) Joshua D. Welch et al. NUCLEIC ACIDS RESEARCH
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- (2016) Jinmiao Chen et al. Nature Communications
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- (2016) Iain C. Macaulay et al. Cell Reports
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- (2016) Kieran R. Campbell et al. PLoS Computational Biology
- 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
- Design and Analysis of Single-Cell Sequencing Experiments
- (2015) Dominic Grün et al. CELL
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- (2014) Sébastien A Smallwood et al. NATURE METHODS
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- (2014) Dominic Grün et al. NATURE METHODS
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- (2014) Peter V Kharchenko et al. NATURE METHODS
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- (2014) Jeffrey T. Leek NUCLEIC ACIDS RESEARCH
- Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape
- (2014) Eugenio Marco et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
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- WGCNA: an R package for weighted correlation network analysis
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- (2008) Arjun Raj et al. NATURE METHODS
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