RNASeqR: an R package for automated two-group RNA-Seq analysis workflow
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Tzu-Pin Lu | Eric Y. Chuang | Liang-Chuan Lai | Mong-Hsun Tsai | Yi-Fang Lee | Chien-Yueh Lee | Kuan-Hao Chao | Yi-Wen Hsiao | E. Chuang | M. Tsai | L. Lai | Chien-Yueh Lee | T. Lu | Yi-Fang Lee | Yi-Wen Hsiao | K. Chao | Kuan-Hao Chao
[1] Susumu Goto,et al. KEGG: Kyoto Encyclopedia of Genes and Genomes , 2000, Nucleic Acids Res..
[2] Michael Q. Zhang,et al. OLego: fast and sensitive mapping of spliced mRNA-Seq reads using small seeds , 2013, Nucleic acids research.
[3] Cedric E. Ginestet. ggplot2: Elegant Graphics for Data Analysis , 2011 .
[4] M. Gerstein,et al. RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.
[5] Dong-Hyung Cho,et al. A nineteen gene‐based risk score classifier predicts prognosis of colorectal cancer patients , 2014, Molecular oncology.
[6] Jean YH Yang,et al. Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.
[7] Carole A. Goble,et al. Taverna: a tool for building and running workflows of services , 2006, Nucleic Acids Res..
[8] Guangchuang Yu,et al. clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.
[9] Florian Hahne,et al. QuasR: quantification and annotation of short reads in R , 2015, Bioinform..
[10] Olaf Wolkenhauer,et al. TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation , 2016, BMC Bioinformatics.
[11] Alex E. Lash,et al. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..
[12] Sébastien Lê,et al. FactoMineR: An R Package for Multivariate Analysis , 2008 .
[13] B. Williams,et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq , 2008, Nature Methods.
[14] Oliver Hofmann,et al. bcbioRNASeq: R package for bcbio RNA-seq analysis , 2017, F1000Research.
[15] Renan Valieris,et al. Bioconda: sustainable and comprehensive software distribution for the life sciences , 2018, Nature Methods.
[16] Andrew Johnston,et al. Transcriptome analysis of psoriasis in a large case-control sample: RNA-seq provides insights into disease mechanisms , 2014, The Journal of investigative dermatology.
[17] J. Davis. Bioinformatics and Computational Biology Solutions Using R and Bioconductor , 2007 .
[18] Steffi Oesterreich,et al. Discovery of naturally occurring ESR1 mutations in breast cancer cell lines modelling endocrine resistance , 2017, Nature Communications.
[19] Dapeng Wang,et al. hppRNA - a Snakemake-based handy parameter-free pipeline for RNA-Seq analysis of numerous samples , 2017, Briefings Bioinform..
[20] Hiroyuki Ogata,et al. KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..
[21] P. Green,et al. Base-calling of automated sequencer traces using phred. I. Accuracy assessment. , 1998, Genome research.
[22] Alexandru I. Tomescu,et al. A novel min-cost flow method for estimating transcript expression with RNA-Seq , 2013, BMC Bioinformatics.
[23] Carlos Guzman,et al. CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction , 2017, BMC Bioinformatics.
[24] Alyssa C. Frazee,et al. Flexible analysis of transcriptome assemblies with Ballgown , 2014, bioRxiv.
[25] Hadley Wickham,et al. ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .
[26] S. Eschrich,et al. Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures , 2017, International journal of genomics.
[27] Jinjie Cui,et al. Lipidomics and RNA-Seq Study of Lipid Regulation in Aphis gossypii parasitized by Lysiphlebia japonica , 2017, Scientific Reports.
[28] P Green,et al. Base-calling of automated sequencer traces using phred. II. Error probabilities. , 1998, Genome research.
[29] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[30] Wolfgang Huber,et al. Love MI, Huber W, Anders S.. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 15: 550 , 2014 .
[31] Mark D. Robinson,et al. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..
[32] Cole Trapnell,et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.
[33] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[34] Paolo Di Tommaso,et al. Nextflow enables reproducible computational workflows , 2017, Nature Biotechnology.
[35] Rasko Leinonen,et al. The sequence read archive: explosive growth of sequencing data , 2011, Nucleic Acids Res..
[36] Thomas Girke,et al. systemPipeR: NGS workflow and report generation environment , 2016, BMC Bioinformatics.
[37] Sean R. Davis,et al. NCBI GEO: archive for functional genomics data sets—update , 2012, Nucleic Acids Res..
[38] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[39] M. Wilkins,et al. Transcriptome and network analyses in Saccharomyces cerevisiae reveal that amphotericin B and lactoferrin synergy disrupt metal homeostasis and stress response , 2017, Scientific Reports.
[40] S. Salzberg,et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads , 2015, Nature Biotechnology.
[41] The Gene Ontology Consortium. Expansion of the Gene Ontology knowledgebase and resources , 2016, Nucleic Acids Res..
[42] Alyssa C. Frazee,et al. Ballgown bridges the gap between transcriptome assembly and expression analysis , 2015, Nature Biotechnology.
[43] The Gene Ontology Consortium,et al. Expansion of the Gene Ontology knowledgebase and resources , 2016, Nucleic Acids Res..
[44] Paul F. Cliften,et al. Base Calling, Read Mapping, and Coverage Analysis , 2015 .
[45] Sven Rahmann,et al. Genome analysis , 2022 .
[46] A. Nekrutenko,et al. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences , 2010, Genome Biology.
[47] Rafael A. Irizarry,et al. Bioinformatics and Computational Biology Solutions using R and Bioconductor , 2005 .
[48] Jie Quan,et al. QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization , 2015, BMC Genomics.
[49] Davis J. McCarthy,et al. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation , 2012, Nucleic acids research.
[50] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[51] Bo Li,et al. VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis , 2018, BMC Bioinformatics.
[52] Alexander Dobin,et al. Mapping RNA‐seq Reads with STAR , 2015, Current protocols in bioinformatics.
[53] Weijun Luo,et al. Pathview: an R/Bioconductor package for pathway-based data integration and visualization , 2013, Bioinform..
[54] Daniel J. Gaffney,et al. A survey of best practices for RNA-seq data analysis , 2016, Genome Biology.
[55] Steven L Salzberg,et al. HISAT: a fast spliced aligner with low memory requirements , 2015, Nature Methods.
[56] S. Lewallen,et al. Epidemiology in practice: case-control studies. , 1998, Community eye health.
[57] Cole Trapnell,et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. , 2010, Nature biotechnology.
[58] Jeffrey T Leek,et al. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown , 2016, Nature Protocols.
[59] Raphael Gottardo,et al. Orchestrating high-throughput genomic analysis with Bioconductor , 2015, Nature Methods.
[60] Roman Valls Guimera,et al. bcbio-nextgen: Automated, distributed next-gen sequencing pipeline , 2012 .