Literature DB >> 31792435

Orchestrating single-cell analysis with Bioconductor.

Robert A Amezquita1, Aaron T L Lun2,3, Etienne Becht1, Vince J Carey4, Lindsay N Carpp1, Ludwig Geistlinger5,6, Federico Marini7,8, Kevin Rue-Albrecht9, Davide Risso10,11, Charlotte Soneson12,13, Levi Waldron5,6, Hervé Pagès1, Mike L Smith14, Wolfgang Huber14, Martin Morgan15, Raphael Gottardo16, Stephanie C Hicks17.   

Abstract

Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.

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Mesh：

Year:  2019        PMID： 31792435      PMCID： PMC7358058          DOI： 10.1038/s41592-019-0654-x

Source DB:  PubMed          Journal:  Nat Methods        ISSN： 1548-7091            Impact factor:   28.547


  79 in total

1.  RNA Sequencing and Analysis.

Authors:  Kimberly R Kukurba; Stephen B Montgomery
Journal:  Cold Spring Harb Protoc       Date:  2015-04-13

Review 2.  The technology and biology of single-cell RNA sequencing.

Authors:  Aleksandra A Kolodziejczyk; Jong Kyoung Kim; Valentine Svensson; John C Marioni; Sarah A Teichmann
Journal:  Mol Cell       Date:  2015-05-21       Impact factor: 17.970

Review 3.  Orchestrating high-throughput genomic analysis with Bioconductor.

Authors:  Wolfgang Huber; Vincent J Carey; Robert Gentleman; Simon Anders; Marc Carlson; Benilton S Carvalho; Hector Corrada Bravo; Sean Davis; Laurent Gatto; Thomas Girke; Raphael Gottardo; Florian Hahne; Kasper D Hansen; Rafael A Irizarry; Michael Lawrence; Michael I Love; James MacDonald; Valerie Obenchain; Andrzej K Oleś; Hervé Pagès; Alejandro Reyes; Paul Shannon; Gordon K Smyth; Dan Tenenbaum; Levi Waldron; Martin Morgan
Journal:  Nat Methods       Date:  2015-02       Impact factor: 28.547

4.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

Authors:  Martin J Aryee; Andrew E Jaffe; Hector Corrada-Bravo; Christine Ladd-Acosta; Andrew P Feinberg; Kasper D Hansen; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2014-01-28       Impact factor: 6.937

5.  limma powers differential expression analyses for RNA-sequencing and microarray studies.

Authors:  Matthew E Ritchie; Belinda Phipson; Di Wu; Yifang Hu; Charity W Law; Wei Shi; Gordon K Smyth
Journal:  Nucleic Acids Res       Date:  2015-01-20       Impact factor: 16.971

6.  Software for computing and annotating genomic ranges.

Authors:  Michael Lawrence; Wolfgang Huber; Hervé Pagès; Patrick Aboyoun; Marc Carlson; Robert Gentleman; Martin T Morgan; Vincent J Carey
Journal:  PLoS Comput Biol       Date:  2013-08-08       Impact factor: 4.475

7.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Authors:  Michael I Love; Wolfgang Huber; Simon Anders
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

Review 8.  Next-generation sequencing: advances and applications in cancer diagnosis.

Authors:  Simona Serratì; Simona De Summa; Brunella Pilato; Daniela Petriella; Rosanna Lacalamita; Stefania Tommasi; Rosamaria Pinto
Journal:  Onco Targets Ther       Date:  2016-12-02       Impact factor: 4.147

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

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

Review 10.  Recent advances in ChIP-seq analysis: from quality management to whole-genome annotation.

Authors:  Ryuichiro Nakato; Katsuhiko Shirahige
Journal:  Brief Bioinform       Date:  2017-03-01       Impact factor: 11.622
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  101 in total

1.  Normalization of Single-Cell RNA-Seq Data.

Authors:  Davide Risso
Journal:  Methods Mol Biol       Date:  2021

2.  Statistical Modeling of High Dimensional Counts.

Authors:  Michael I Love
Journal:  Methods Mol Biol       Date:  2021

Review 3.  Prioritization of cell types responsive to biological perturbations in single-cell data with Augur.

Authors:  Jordan W Squair; Michael A Skinnider; Matthieu Gautier; Leonard J Foster; Grégoire Courtine
Journal:  Nat Protoc       Date:  2021-06-25       Impact factor: 13.491

Review 4.  Tools for the analysis of high-dimensional single-cell RNA sequencing data.

Authors:  Yan Wu; Kun Zhang
Journal:  Nat Rev Nephrol       Date:  2020-03-27       Impact factor: 28.314

5.  CCPE: cell cycle pseudotime estimation for single cell RNA-seq data.

Authors:  Jiajia Liu; Mengyuan Yang; Weiling Zhao; Xiaobo Zhou
Journal:  Nucleic Acids Res       Date:  2022-01-25       Impact factor: 16.971

6.  dittoSeq: Universal User-Friendly Single-Cell and Bulk RNA Sequencing Visualization Toolkit.

Authors:  Daniel G Bunis; Jared Andrews; Gabriela K Fragiadakis; Trevor D Burt; Marina Sirota
Journal:  Bioinformatics       Date:  2020-12-12       Impact factor: 6.937

7.  Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data.

Authors:  Nan Miles Xi; Jingyi Jessica Li
Journal:  Cell Syst       Date:  2020-12-17       Impact factor: 10.304

8.  Transcriptional signature in microglia associated with Aβ plaque phagocytosis.

Authors:  Alexandra Grubman; Xin Yi Choo; Gabriel Chew; John F Ouyang; Guizhi Sun; Nathan P Croft; Fernando J Rossello; Rebecca Simmons; Sam Buckberry; Dulce Vargas Landin; Jahnvi Pflueger; Teresa H Vandekolk; Zehra Abay; Yichen Zhou; Xiaodong Liu; Joseph Chen; Michael Larcombe; John M Haynes; Catriona McLean; Sarah Williams; Siew Yeen Chai; Trevor Wilson; Ryan Lister; Colin W Pouton; Anthony W Purcell; Owen J L Rackham; Enrico Petretto; Jose M Polo
Journal:  Nat Commun       Date:  2021-05-21       Impact factor: 14.919

Review 9.  A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis.

Authors:  Aleksandr Bobrovskikh; Alexey Doroshkov; Stefano Mazzoleni; Fabrizio Cartenì; Francesco Giannino; Ulyana Zubairova
Journal:  Front Genet       Date:  2021-05-21       Impact factor: 4.599

10.  Multiomic Analysis of Subtype Evolution and Heterogeneity in High-Grade Serous Ovarian Carcinoma.

Authors:  Ludwig Geistlinger; Sehyun Oh; Marcel Ramos; Lucas Schiffer; Rebecca S LaRue; Christine M Henzler; Sarah A Munro; Claire Daughters; Andrew C Nelson; Boris J Winterhoff; Zenas Chang; Shobhana Talukdar; Mihir Shetty; Sally A Mullany; Martin Morgan; Giovanni Parmigiani; Michael J Birrer; Li-Xuan Qin; Markus Riester; Timothy K Starr; Levi Waldron
Journal:  Cancer Res       Date:  2020-08-03       Impact factor: 12.701
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