Guidelines for Setting Up a mRNA Sequencing Experiment and Best Practices for Bioinformatic Data Analysis.
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Nunzio D'Agostino | Teresa Rosa Galise | Salvatore Esposito | N. D’Agostino | S. Esposito | T. R. Galise
[1] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[2] E. Liu,et al. 5' Long serial analysis of gene expression (LongSAGE) and 3' LongSAGE for transcriptome characterization and genome annotation. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[3] Jian-Kang Zhu,et al. Rapid phosphatidic acid accumulation in response to low temperature stress in Arabidopsis is generated through diacylglycerol kinase , 2013, Front. Plant Sci..
[4] The Uniprot Consortium. UniProt: the universal protein knowledgebase , 2018, Nucleic acids research.
[5] Matthew D. Young,et al. Gene ontology analysis for RNA-seq: accounting for selection bias , 2010, Genome Biology.
[6] Marshall Nichols,et al. Comparing reference-based RNA-Seq mapping methods for non-human primate data , 2014, BMC Genomics.
[7] Steve Horvath,et al. WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.
[8] Richard Durbin,et al. Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .
[9] Elena Bushmanova,et al. rnaQUAST: a quality assessment tool for de novo transcriptome assemblies , 2016, Bioinform..
[10] E. Shapiro,et al. Single-cell sequencing-based technologies will revolutionize whole-organism science , 2013, Nature Reviews Genetics.
[11] Peter Winter,et al. Gene expression analysis of plant host–pathogen interactions by SuperSAGE , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[12] Matthew Fraser,et al. InterProScan 5: genome-scale protein function classification , 2014, Bioinform..
[13] Daniel Spies,et al. Comparative analysis of differential gene expression tools for RNA sequencing time course data , 2017, Briefings Bioinform..
[14] B. Haas,et al. Advancing RNA-Seq analysis , 2010, Nature Biotechnology.
[15] Martin Vingron,et al. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels , 2012, Bioinform..
[16] Susanne A. Fritz,et al. Correlates of Recent Declines of Rodents in Northern and Southern Australia: Habitat Structure Is Critical , 2015, PloS one.
[17] Luyi Tian,et al. Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments , 2019, Nature Methods.
[18] Simon Andrews,et al. FastQ Screen: A tool for multi-genome mapping and quality control , 2018, F1000Research.
[19] R. Sathishkumar,et al. Stress-Induced Accumulation of DcAOX1 and DcAOX2a Transcripts Coincides with Critical Time Point for Structural Biomass Prediction in Carrot Primary Cultures (Daucus carota L.) , 2016, Front. Genet..
[20] C. Billington,et al. Orexin activation counteracts decreases in nonexercise activity thermogenesis (NEAT) caused by high-fat diet , 2017, Physiology & Behavior.
[21] The UniProt Consortium,et al. UniProt: a worldwide hub of protein knowledge , 2018, Nucleic Acids Res..
[22] Nicolas Servant,et al. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis , 2013, Briefings Bioinform..
[23] S. Fields,et al. Dynamics of Gene Expression in Single Root Cells of Arabidopsis thaliana. , 2019, The Plant cell.
[24] Kenneth D. Birnbaum,et al. The potential of single-cell profiling in plants , 2016, Genome Biology.
[25] Marcel H. Schulz,et al. Informed kmer selection for de novo transcriptome assembly , 2015, Bioinform..
[26] S. Cockell. Gene Set Enrichment Analysis , 2011 .
[27] John Quackenbush,et al. WebMeV: a Cloud Platform for Analyzing and Visualizing Cancer Genomic Data , 2017, bioRxiv.
[28] A. Conesa,et al. Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package , 2015, Nucleic acids research.
[29] Ronald W. Davis,et al. Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.
[30] Wei Shi,et al. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features , 2013, Bioinform..
[31] Neva C. Durand,et al. Hybrid de novo genome assembly and centromere characterization of the gray mouse lemur (Microcebus murinus) , 2017, BMC Biology.
[32] Paul Theodor Pyl,et al. HTSeq—a Python framework to work with high-throughput sequencing data , 2014, bioRxiv.
[33] Steven L Salzberg,et al. HISAT: a fast spliced aligner with low memory requirements , 2015, Nature Methods.
[34] Anna Y. Tang,et al. Biological significance of RNA-seq and single-cell genomic research in woody plants , 2019, Journal of Forestry Research.
[35] Gilles Celeux,et al. Data-based filtering for replicated high-throughput transcriptome sequencing experiments , 2013, Bioinform..
[36] Z. Fei,et al. Catalyzing plant science research with RNA-seq , 2013, Front. Plant Sci..
[37] Amos Bairoch,et al. The ENZYME database in 2000 , 2000, Nucleic Acids Res..
[38] Patrick J. Biggs,et al. SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data , 2010, BMC Bioinformatics.
[39] Daniel Nilsson,et al. An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge , 2014, Genome Biology.
[40] Manja Marz,et al. De novo transcriptome assembly: A comprehensive cross-species comparison of short-read RNA-Seq assemblers , 2019, GigaScience.
[41] A. Kerlavage,et al. Complementary DNA sequencing: expressed sequence tags and human genome project , 1991, Science.
[42] Marcel E Dinger,et al. Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data , 2017, Scientific Reports.
[43] Nuno A. Fonseca,et al. Tools for mapping high-throughput sequencing data , 2012, Bioinform..
[44] Emily M. Strait,et al. The arabidopsis information resource: Making and mining the “gold standard” annotated reference plant genome , 2015, Genesis.
[45] Caroline C. Friedel,et al. A Comprehensive Evaluation of Alignment Algorithms in the Context of RNA-Seq , 2012, PloS one.
[46] Suzanna E Lewis,et al. JBrowse: a dynamic web platform for genome visualization and analysis , 2016, Genome Biology.
[47] Tyson A. Clark,et al. Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing , 2016, Nature Communications.
[48] Mark D. Robinson,et al. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..
[49] Kin-Fan Au,et al. PacBio Sequencing and Its Applications , 2015, Genom. Proteom. Bioinform..
[50] Charlotte Soneson,et al. A comparison of methods for differential expression analysis of RNA-seq data , 2013, BMC Bioinformatics.
[51] Angela N. Brooks,et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles , 2017, Cell.
[52] Gene expression profiling of tomato roots interacting with Pseudomonas fluorescens unravels the molecular reprogramming that occurs during the early phases of colonization , 2019, Symbiosis.
[53] Michele Tumminello,et al. RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets , 2019, BMC Bioinformatics.
[54] Qian Li,et al. Comparison of normalization approaches for gene expression studies completed with high-throughput sequencing , 2018, PloS one.
[55] John Quackenbush,et al. The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes , 2004, Nucleic Acids Res..
[56] Daniel Soudry,et al. Bifurcation analysis of two coupled Jansen-Rit neural mass models , 2018, PloS one.
[57] N. D’Agostino,et al. SolEST database: a "one-stop shop" approach to the study of Solanaceae transcriptomes , 2009, BMC Plant Biology.
[58] Colin N. Dewey,et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis , 2013, Nature Protocols.
[59] Xiandong Meng,et al. Widespread Polycistronic Transcripts in Fungi Revealed by Single-Molecule mRNA Sequencing , 2015, PloS one.
[60] C. Tyler-Smith,et al. Ancient DNA and the rewriting of human history: be sparing with Occam’s razor , 2016, Genome Biology.
[61] C. Mason,et al. Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data , 2013, Genome Biology.
[62] Thomas Ragg,et al. The RIN: an RNA integrity number for assigning integrity values to RNA measurements , 2006, BMC Molecular Biology.
[63] S. Banerjee,et al. Targeted Next Generation Sequencing Revealed a Novel Homozygous Loss-of-Function Mutation in ILDR1 Gene Causes Autosomal Recessive Nonsyndromic Sensorineural Hearing Loss in a Chinese Family , 2019, Front. Genet..
[64] Holger Heyn,et al. Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies , 2018, Nature Protocols.
[65] P. Walsh,et al. Simultaneous Amplification and Detection of Specific DNA Sequences , 1992, Bio/Technology.
[66] M. Hemberg,et al. Challenges in unsupervised clustering of single-cell RNA-seq data , 2019, Nature Reviews Genetics.
[67] N. Friedman,et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data , 2011, Nature Biotechnology.
[68] Yuki Moriya,et al. KAAS: an automatic genome annotation and pathway reconstruction server , 2007, Nucleic Acids Res..
[69] B. Williams,et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq , 2008, Nature Methods.
[70] Yvan Saeys,et al. A comparison of single-cell trajectory inference methods , 2019, Nature Biotechnology.
[71] Claudio Lottaz,et al. FastqPuri: high-performance preprocessing of RNA-seq data , 2018, BMC Bioinformatics.
[72] B. Elmoualij,et al. A decade of improvements in quantification of gene expression and internal standard selection. , 2009, Biotechnology advances.
[73] Nneka Emenyonu,et al. Rethinking the “Pre” in Pre-Therapy Counseling: No Benefit of Additional Visits Prior to Therapy on Adherence or Viremia in Ugandans Initiating ARVs , 2012, PloS one.
[74] S A Bustin,et al. Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. , 2002, Journal of molecular endocrinology.
[75] S. Ott,et al. Single-Cell Transcriptomics: A High-Resolution Avenue for Plant Functional Genomics. , 2019, Trends in plant science.
[76] N. El-Mabrouk,et al. Gene order alignment on trees with multiOrthoAlign , 2014, BMC Genomics.
[77] M. Robles,et al. University of Birmingham High throughput functional annotation and data mining with the Blast2GO suite , 2022 .
[78] H. Duncan,et al. Histone Acetylation as a Regenerative Target in the Dentine-Pulp Complex , 2020, Frontiers in Genetics.
[79] Geng Chen,et al. Single-Cell RNA-Seq Technologies and Related Computational Data Analysis , 2019, Front. Genet..
[80] Brad T. Sherman,et al. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.
[81] A. Valsamakis,et al. Comparison of Automated and Manual Nucleic Acid Extraction Methods for Detection of Enterovirus RNA , 2003, Journal of Clinical Microbiology.
[82] B. Tian,et al. RNA‐Seq methods for transcriptome analysis , 2017, Wiley interdisciplinary reviews. RNA.
[83] Riccardo Aiese Cigliano,et al. De Novo Transcriptome Assembly of Cucurbita Pepo L. Leaf Tissue Infested by Aphis Gossypii , 2018, Data.
[84] David Stephen Horner,et al. SMRT long reads and Direct Label and Stain optical maps allow the generation of a high-quality genome assembly for the European barn swallow (Hirundo rustica rustica) , 2018, bioRxiv.
[85] Rob Patro,et al. Salmon provides fast and bias-aware quantification of transcript expression , 2017, Nature Methods.
[86] Yongsheng Bai,et al. Evaluation of de novo transcriptome assemblies from RNA-Seq data , 2014, Genome Biology.
[87] Cole Trapnell,et al. Computational methods for transcriptome annotation and quantification using RNA-seq , 2011, Nature Methods.
[88] Travers Ching,et al. Single-Cell Transcriptomics Bioinformatics and Computational Challenges , 2016, Front. Genet..
[89] Wei Li,et al. RSeQC: quality control of RNA-seq experiments , 2012, Bioinform..
[90] C. V. Jongeneel,et al. ESTScan: A Program for Detecting, Evaluating, and Reconstructing Potential Coding Regions in EST Sequences , 1999, ISMB.
[91] R. Farrell. Isolation of Polyadenylated RNA , 2010 .
[92] Peter F Stadler,et al. Chromatin measurements reveal contributions of synthesis and decay to steady-state mRNA levels , 2012 .
[93] James C. Hu,et al. The Gene Ontology Resource: 20 years and still GOing strong , 2019 .
[94] Nicolas Faivre,et al. Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions , 2017, BMC Biology.
[95] Allon M. Klein,et al. Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.
[96] Colin N. Dewey,et al. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome , 2011, BMC Bioinformatics.
[97] N. Friedman,et al. Comprehensive comparative analysis of strand-specific RNA sequencing methods , 2010, Nature Methods.
[98] C. Auffray,et al. The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics. , 1999, Genome research.
[99] Rithy K. Roth,et al. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays , 2000, Nature Biotechnology.
[100] Yixing Han,et al. Advanced Applications of RNA Sequencing and Challenges , 2015, Bioinformatics and biology insights.
[101] Zhengwei Zhu,et al. CD-HIT: accelerated for clustering the next-generation sequencing data , 2012, Bioinform..
[102] Silvio C. E. Tosatto,et al. InterPro in 2019: improving coverage, classification and access to protein sequence annotations , 2018, Nucleic Acids Res..
[103] Adrian Alexa,et al. Gene set enrichment analysis with topGO , 2006 .
[104] Robert D. Finn,et al. Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families , 2017, Nucleic Acids Res..
[105] Akiyasu C. Yoshizawa,et al. KAAS: an automatic genome annotation and pathway reconstruction server , 2007, Environmental health perspectives.
[106] Luigi Frusciante,et al. TomatEST database: in silico exploitation of EST data to explore expression patterns in tomato species , 2006, Nucleic Acids Res..
[107] Matthew D. Wilkerson,et al. PlantGDB: a resource for comparative plant genomics , 2007, Nucleic Acids Res..
[108] J. Harrow,et al. Assessment of transcript reconstruction methods for RNA-seq , 2013, Nature Methods.
[109] Zhou Du,et al. agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update , 2017, Nucleic Acids Res..
[110] L. Pachter,et al. Streaming fragment assignment for real-time analysis of sequencing experiments , 2012, Nature Methods.
[111] Matthew D. Young,et al. From RNA-seq reads to differential expression results , 2010, Genome Biology.
[112] J. Lee,et al. Single-cell RNA sequencing technologies and bioinformatics pipelines , 2018, Experimental & Molecular Medicine.
[113] Cole Trapnell,et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. , 2010, Nature biotechnology.
[114] M. Boguski,et al. dbEST — database for “expressed sequence tags” , 1993, Nature Genetics.
[115] Günter P. Wagner,et al. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples , 2012, Theory in Biosciences.
[116] Cole Trapnell,et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.
[117] Israel Steinfeld,et al. BMC Bioinformatics BioMed Central , 2008 .
[118] M. Gerstein,et al. RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.
[119] Lingling An,et al. Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey , 2020, Frontiers in Genetics.
[120] Gonçalo R. Abecasis,et al. The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..
[121] K. Kinzler,et al. Serial Analysis of Gene Expression , 1995, Science.
[122] Wei Zhou,et al. Characterization of the Yeast Transcriptome , 1997, Cell.
[123] R. Doerge,et al. Statistical Design and Analysis of RNA Sequencing Data , 2010, Genetics.
[124] W. Barbazuk,et al. Genome-wide analyses of alternative splicing in plants: opportunities and challenges. , 2008, Genome research.
[125] M. Robinson,et al. A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.
[126] D. Corey,et al. RNA sequencing: platform selection, experimental design, and data interpretation. , 2012, Nucleic acid therapeutics.
[127] Chia-Wei Chen,et al. OPATs: Omnibus P-value association tests , 2017, Briefings Bioinform..
[128] C. Pieterse,et al. RNA-Seq: revelation of the messengers. , 2013, Trends in plant science.
[129] Sara Ballouz,et al. Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies , 2009, BMC Bioinformatics.
[130] Evan Z. Macosko,et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.
[131] C. Peres,et al. Conservation performance of different conservation governance regimes in the Peruvian Amazon , 2017, Scientific Reports.
[132] Application of circular consensus sequencing and network analysis to characterize the bovine IgG repertoire , 2012, BMC Immunology.
[133] K. Hansen,et al. Sequencing technology does not eliminate biological variability , 2011, Nature Biotechnology.
[134] S. Kelly,et al. TransRate: reference-free quality assessment of de novo transcriptome assemblies , 2015, bioRxiv.
[135] Helga Thorvaldsdóttir,et al. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration , 2012, Briefings Bioinform..
[136] Thomas Hackl,et al. proovread: large-scale high-accuracy PacBio correction through iterative short read consensus , 2014, Bioinform..
[137] Peter M. Rice,et al. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants , 2009, Nucleic acids research.
[138] S. Rhee,et al. MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. , 2004, The Plant journal : for cell and molecular biology.
[139] Steven L Salzberg,et al. Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.
[140] H. Schiöth,et al. Acute sleep deprivation has no lasting effects on the human antibody titer response following a novel influenza A H1N1 virus vaccination , 2012, BMC Immunology.
[141] Peter Langfelder,et al. Fast R Functions for Robust Correlations and Hierarchical Clustering. , 2012, Journal of statistical software.
[142] J. Parkinson,et al. Expressed sequence tags: an overview. , 2009, Methods in molecular biology.
[143] Sandrine Dudoit,et al. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments , 2010, BMC Bioinformatics.
[144] Evgeny M. Zdobnov,et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs , 2015, Bioinform..
[145] Steven J. M. Jones,et al. De novo assembly and analysis of RNA-seq data , 2010, Nature Methods.
[146] J. Hadfield,et al. RNA sequencing: the teenage years , 2019, Nature Reviews Genetics.
[147] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[148] Giuseppe Testa,et al. RNAontheBENCH: computational and empirical resources for benchmarking RNAseq quantification and differential expression methods , 2016, Nucleic acids research.
[149] J. Kawai,et al. Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage , 2003, Proceedings of the National Academy of Sciences of the United States of America.