Literature DB >> 32926366

Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments.

Xiaoqing Yu1, Farnoosh Abbas-Aghababazadeh1, Y Ann Chen1, Brooke L Fridley2.   

Abstract

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.

Entities:  

Keywords:  Differential expression; High-throughput sequencing; Normalization; Quality control; Single-cell; Transcriptomics; Tumor heterogeneity

Mesh:

Year:  2021        PMID: 32926366      PMCID: PMC7771369          DOI: 10.1007/978-1-0716-0849-4_9

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  166 in total

1.  De novo assembly and analysis of RNA-seq data.

Authors:  Gordon Robertson; Jacqueline Schein; Readman Chiu; Richard Corbett; Matthew Field; Shaun D Jackman; Karen Mungall; Sam Lee; Hisanaga Mark Okada; Jenny Q Qian; Malachi Griffith; Anthony Raymond; Nina Thiessen; Timothee Cezard; Yaron S Butterfield; Richard Newsome; Simon K Chan; Rong She; Richard Varhol; Baljit Kamoh; Anna-Liisa Prabhu; Angela Tam; YongJun Zhao; Richard A Moore; Martin Hirst; Marco A Marra; Steven J M Jones; Pamela A Hoodless; Inanc Birol
Journal:  Nat Methods       Date:  2010-10-10       Impact factor: 28.547

Review 2.  The challenges of sequencing by synthesis.

Authors:  Carl W Fuller; Lyle R Middendorf; Steven A Benner; George M Church; Timothy Harris; Xiaohua Huang; Stevan B Jovanovich; John R Nelson; Jeffery A Schloss; David C Schwartz; Dmitri V Vezenov
Journal:  Nat Biotechnol       Date:  2009-11-06       Impact factor: 54.908

3.  Differential expression in RNA-seq: a matter of depth.

Authors:  Sonia Tarazona; Fernando García-Alcalde; Joaquín Dopazo; Alberto Ferrer; Ana Conesa
Journal:  Genome Res       Date:  2011-09-08       Impact factor: 9.043

4.  Normalization and noise reduction for single cell RNA-seq experiments.

Authors:  Bo Ding; Lina Zheng; Yun Zhu; Nan Li; Haiyang Jia; Rizi Ai; Andre Wildberg; Wei Wang
Journal:  Bioinformatics       Date:  2015-02-24       Impact factor: 6.937

5.  A two-parameter generalized Poisson model to improve the analysis of RNA-seq data.

Authors:  Sudeep Srivastava; Liang Chen
Journal:  Nucleic Acids Res       Date:  2010-07-29       Impact factor: 16.971

6.  Understanding mechanisms underlying human gene expression variation with RNA sequencing.

Authors:  Joseph K Pickrell; John C Marioni; Athma A Pai; Jacob F Degner; Barbara E Engelhardt; Everlyne Nkadori; Jean-Baptiste Veyrieras; Matthew Stephens; Yoav Gilad; Jonathan K Pritchard
Journal:  Nature       Date:  2010-03-10       Impact factor: 49.962

7.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

8.  Mpath maps multi-branching single-cell trajectories revealing progenitor cell progression during development.

Authors:  Jinmiao Chen; Andreas Schlitzer; Svetoslav Chakarov; Florent Ginhoux; Michael Poidinger
Journal:  Nat Commun       Date:  2016-06-30       Impact factor: 14.919

9.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

10.  Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage.

Authors:  Dvir Aran; Agnieszka P Looney; Leqian Liu; Esther Wu; Valerie Fong; Austin Hsu; Suzanna Chak; Ram P Naikawadi; Paul J Wolters; Adam R Abate; Atul J Butte; Mallar Bhattacharya
Journal:  Nat Immunol       Date:  2019-01-14       Impact factor: 25.606

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  2 in total

Review 1.  A Detailed Overview About the Single-Cell Analyses of Solid Tumors Focusing on Colorectal Cancer.

Authors:  William J Kothalawala; Barbara K Barták; Zsófia B Nagy; Sára Zsigrai; Krisztina A Szigeti; Gábor Valcz; István Takács; Alexandra Kalmár; Béla Molnár
Journal:  Pathol Oncol Res       Date:  2022-07-14       Impact factor: 2.874

Review 2.  Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data.

Authors:  Christopher M Wilson; Oscar E Ospina; Mary K Townsend; Jonathan Nguyen; Carlos Moran Segura; Joellen M Schildkraut; Shelley S Tworoger; Lauren C Peres; Brooke L Fridley
Journal:  Cancers (Basel)       Date:  2021-06-17       Impact factor: 6.575

  2 in total

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