Beta-Poisson model for single-cell RNA-seq data analyses (Q31092320)

28 June 2017

title

Beta-Poisson model for single-cell RNA-seq data analyses (English)

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28 June 2017

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Trung Nghia Vu

1

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Krishna R Kalari

object named as

Krishna R Kalari

3

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Yudi Pawitan

7

object named as

Yudi Pawitan

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28 June 2017

Quin F Wills

2

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28 June 2017

Nifang Niu

4

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28 June 2017

Liewei Wang

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28 June 2017

Mattias Rantalainen

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28 June 2017

language of work or name

English

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publication date

19 April 2016

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28 June 2017

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28 June 2017

volume

32

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28 June 2017

issue

14

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28 June 2017

page(s)

2128-2135

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Count-based differential expression analysis of RNA sequencing data using R and Bioconductor

28 June 2017

cites work

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https://api.crossref.org/works/10.1093%2FBIOINFORMATICS%2FBTW202

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Inferring single-cell gene expression mechanisms using stochastic simulation

21 January 2018

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MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data

21 January 2018

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Bayesian approach to single-cell differential expression analysis

21 January 2018

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Distinct perturbation of the translatome by the antidiabetic drug metformin

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

21 January 2018

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

21 January 2018

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Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms

21 January 2018

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False discovery rate, sensitivity and sample size for microarray studies.

21 January 2018

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

21 January 2018

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Stochastic models of transcription: from single molecules to single cells

21 January 2018

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Analytical distributions for stochastic gene expression

21 January 2018

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Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

21 January 2018

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Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

21 January 2018

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Single-cell polyadenylation site mapping reveals 3' isoform choice variability

21 January 2018

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Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments

21 January 2018

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Quantitative assessment of single-cell RNA-sequencing methods.

21 January 2018

1 reference

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10.1093/BIOINFORMATICS/BTW202

21 January 2018

Identifiers

DOI

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journals/bioinformatics/VuWKNWRP16

28 June 2017

DBLP publication ID

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DBLP Dataset 2021-01-02

28 January 2021

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