Literature DB >> 22383036

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

Cole Trapnell1, Adam Roberts, Loyal Goff, Geo Pertea, Daehwan Kim, David R Kelley, Harold Pimentel, Steven L Salzberg, John L Rinn, Lior Pachter.   

Abstract

Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.

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Year:  2012        PMID: 22383036      PMCID: PMC3334321          DOI: 10.1038/nprot.2012.016

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  42 in total

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Journal:  Nat Methods       Date:  2010-10-10       Impact factor: 28.547

2.  Stem cell transcriptome profiling via massive-scale mRNA sequencing.

Authors:  Nicole Cloonan; Alistair R R Forrest; Gabriel Kolle; Brooke B A Gardiner; Geoffrey J Faulkner; Mellissa K Brown; Darrin F Taylor; Anita L Steptoe; Shivangi Wani; Graeme Bethel; Alan J Robertson; Andrew C Perkins; Stephen J Bruce; Clarence C Lee; Swati S Ranade; Heather E Peckham; Jonathan M Manning; Kevin J McKernan; Sean M Grimmond
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

Review 3.  Computational methods for transcriptome annotation and quantification using RNA-seq.

Authors:  Manuel Garber; Manfred G Grabherr; Mitchell Guttman; Cole Trapnell
Journal:  Nat Methods       Date:  2011-05-27       Impact factor: 28.547

4.  Analysis and design of RNA sequencing experiments for identifying isoform regulation.

Authors:  Yarden Katz; Eric T Wang; Edoardo M Airoldi; Christopher B Burge
Journal:  Nat Methods       Date:  2010-11-07       Impact factor: 28.547

5.  Biases in Illumina transcriptome sequencing caused by random hexamer priming.

Authors:  Kasper D Hansen; Steven E Brenner; Sandrine Dudoit
Journal:  Nucleic Acids Res       Date:  2010-04-14       Impact factor: 16.971

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Authors:  David S Johnson; Ali Mortazavi; Richard M Myers; Barbara Wold
Journal:  Science       Date:  2007-05-31       Impact factor: 47.728

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Authors:  Nicholas T Ingolia; Sina Ghaemmaghami; John R S Newman; Jonathan S Weissman
Journal:  Science       Date:  2009-02-12       Impact factor: 47.728

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Authors:  Brenton R Graveley; Angela N Brooks; Joseph W Carlson; Michael O Duff; Jane M Landolin; Li Yang; Carlo G Artieri; Marijke J van Baren; Nathan Boley; Benjamin W Booth; James B Brown; Lucy Cherbas; Carrie A Davis; Alex Dobin; Renhua Li; Wei Lin; John H Malone; Nicolas R Mattiuzzo; David Miller; David Sturgill; Brian B Tuch; Chris Zaleski; Dayu Zhang; Marco Blanchette; Sandrine Dudoit; Brian Eads; Richard E Green; Ann Hammonds; Lichun Jiang; Phil Kapranov; Laura Langton; Norbert Perrimon; Jeremy E Sandler; Kenneth H Wan; Aarron Willingham; Yu Zhang; Yi Zou; Justen Andrews; Peter J Bickel; Steven E Brenner; Michael R Brent; Peter Cherbas; Thomas R Gingeras; Roger A Hoskins; Thomas C Kaufman; Brian Oliver; Susan E Celniker
Journal:  Nature       Date:  2010-12-22       Impact factor: 49.962

9.  Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.

Authors:  Jeremy Goecks; Anton Nekrutenko; James Taylor
Journal:  Genome Biol       Date:  2010-08-25       Impact factor: 13.583

10.  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

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  2000 in total

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Journal:  J Biol Chem       Date:  2014-11-14       Impact factor: 5.157

2.  Transcriptomic analysis of hookworm Ancylostoma ceylanicum life cycle stages reveals changes in G-protein coupled receptor diversity associated with the onset of parasitism.

Authors:  James P Bernot; Gabriella Rudy; Patti T Erickson; Ramesh Ratnappan; Meseret Haile; Bruce A Rosa; Makedonka Mitreva; Damien M O'Halloran; John M Hawdon
Journal:  Int J Parasitol       Date:  2020-06-25       Impact factor: 3.981

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Authors:  Tiffany M Lowe-Power; Connor G Hendrich; Edda von Roepenack-Lahaye; Bin Li; Dousheng Wu; Raka Mitra; Beth L Dalsing; Patrizia Ricca; Jacinth Naidoo; David Cook; Amy Jancewicz; Patrick Masson; Bart Thomma; Thomas Lahaye; Anthony J Michael; Caitilyn Allen
Journal:  Environ Microbiol       Date:  2017-12-22       Impact factor: 5.491

4.  Exploiting Natural Variation to Uncover an Alkene Biosynthetic Enzyme in Poplar.

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Journal:  Plant Cell       Date:  2017-07-20       Impact factor: 11.277

5.  Thioredoxin-Mediated ROS Homeostasis Explains Natural Variation in Plant Regeneration.

Authors:  Hui Zhang; Ting Ting Zhang; Hui Liu; De Ying Shi; Meng Wang; Xiao Min Bie; Xing Guo Li; Xian Sheng Zhang
Journal:  Plant Physiol       Date:  2018-01-29       Impact factor: 8.340

6.  Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials.

Authors:  Travis S Johnson; Sihong Li; Jonathan R Kho; Kun Huang; Yan Zhang
Journal:  Pac Symp Biocomput       Date:  2018

7.  Birth of a new gene on the Y chromosome of Drosophila melanogaster.

Authors:  Antonio Bernardo Carvalho; Beatriz Vicoso; Claudia A M Russo; Bonnielin Swenor; Andrew G Clark
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-18       Impact factor: 11.205

8.  Nfatc1 orchestrates aging in hair follicle stem cells.

Authors:  Brice E Keyes; Jeremy P Segal; Evan Heller; Wen-Hui Lien; Chiung-Ying Chang; Xingyi Guo; Dan S Oristian; Deyou Zheng; Elaine Fuchs
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-26       Impact factor: 11.205

9.  Targeting PLK1 overcomes T-DM1 resistance via CDK1-dependent phosphorylation and inactivation of Bcl-2/xL in HER2-positive breast cancer.

Authors:  Özge Saatci; Simone Borgoni; Özge Akbulut; Selvi Durmuş; Umar Raza; Erol Eyüpoğlu; Can Alkan; Aytekin Akyol; Özgür Kütük; Stefan Wiemann; Özgür Şahin
Journal:  Oncogene       Date:  2018-02-02       Impact factor: 9.867

10.  RNentropy: an entropy-based tool for the detection of significant variation of gene expression across multiple RNA-Seq experiments.

Authors:  Federico Zambelli; Francesca Mastropasqua; Ernesto Picardi; Anna Maria D'Erchia; Graziano Pesole; Giulio Pavesi
Journal:  Nucleic Acids Res       Date:  2018-05-04       Impact factor: 16.971

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