3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism
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[1] Michael T. Simonich,et al. Transcriptomic and Long-Term Behavioral Deficits Associated with Developmental 3.5 GHz Radiofrequency Radiation Exposures in Zebrafish. , 2022, Environmental science & technology letters.
[2] J. Field,et al. Sulfonamide functional head on short-chain perfluorinated substance drives developmental toxicity , 2022, iScience.
[3] Praveer P Sharma,et al. Single-cell transcriptomic analysis of zebrafish cranial neural crest reveals spatiotemporal regulation of lineage decisions during development , 2021, Cell reports.
[4] Guoji Guo,et al. Characterization of the Zebrafish Cell Landscape at Single-Cell Resolution , 2021, Frontiers in Cell and Developmental Biology.
[5] Lucas E. Wange,et al. Prime-seq, efficient and powerful bulk RNA sequencing , 2021, bioRxiv.
[6] K. Waters,et al. Gene co-expression network analysis in zebrafish reveals chemical class specific modules , 2021, BMC Genomics.
[7] K. Waters,et al. Gene co-expression network analysis in zebrafish reveals chemical class specific modules , 2021, BMC Genomics.
[8] M. Dierssen,et al. Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome , 2021, PLoS Comput. Biol..
[9] S. Tilton,et al. Linking Coregulated Gene Modules with Polycyclic Aromatic Hydrocarbon-Related Cancer Risk in the 3D Human Bronchial Epithelium. , 2021, Chemical research in toxicology.
[10] S. Sumanas,et al. Single-cell transcriptome analysis of the zebrafish embryonic trunk , 2021, bioRxiv.
[11] V. Plagnol,et al. A Comparison of Low Read Depth QuantSeq 3′ Sequencing to Total RNA-Seq in FUS Mutant Mice , 2020, Frontiers in Genetics.
[12] L. Zhu,et al. An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes , 2020, eLife.
[13] Wenlong Huang,et al. A transcriptomics-based analysis of toxicity mechanisms of zebrafish embryos and larvae following parental Bisphenol A exposure. , 2020, Ecotoxicology and environmental safety.
[14] Q. Tu,et al. Decode-seq: a practical approach to improve differential gene expression analysis , 2020, Genome Biology.
[15] Imhoi Koo,et al. Metatranscriptomic Analysis of the Mouse Gut Microbiome Response to the Persistent Organic Pollutant 2,3,7,8-Tetrachlorodibenzofuran , 2019, Metabolites.
[16] Gennady Korotkevich,et al. Fast gene set enrichment analysis , 2019, bioRxiv.
[17] Magnus M Münch,et al. Infection and RNA-seq analysis of a zebrafish tlr2 mutant shows a broad function of this toll-like receptor in transcriptional and metabolic control and defense to Mycobacterium marinum infection , 2019, BMC Genomics.
[18] C. Peng,et al. Identification of Novel MicroRNAs and Characterization of MicroRNA Expression Profiles in Zebrafish Ovarian Follicular Cells , 2019, Front. Endocrinol..
[19] A. Nagano,et al. Lasy-Seq: a high-throughput library preparation method for RNA-Seq and its application in the analysis of plant responses to fluctuating temperatures , 2019, Scientific Reports.
[20] J. Vilo,et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) , 2019, Nucleic Acids Res..
[21] Robert L. Tanguay,et al. Coupling Genome-wide Transcriptomics and Developmental Toxicity Profiles in Zebrafish to Characterize Polycyclic Aromatic Hydrocarbon (PAH) Hazard , 2019, International journal of molecular sciences.
[22] C. Vulpe,et al. A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods , 2019, BMC Genomics.
[23] M. Pellegrini,et al. A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods , 2019, BMC Genomics.
[24] Dongye Zhao,et al. Toxicity and Transcriptome Sequencing (RNA-seq) Analyses of Adult Zebrafish in Response to Exposure Carboxymethyl Cellulose Stabilized Iron Sulfide Nanoparticles , 2018, Scientific Reports.
[25] P. Joseph. Transcriptomics in toxicology. , 2017, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.
[26] Scott C. Wesselkamper,et al. Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment , 2017, Toxicological sciences : an official journal of the Society of Toxicology.
[27] C. Simillion,et al. Avoiding the pitfalls of gene set enrichment analysis with SetRank , 2017, BMC Bioinformatics.
[28] T. Torres,et al. Traditional versus 3′ RNA-seq in a non-model species , 2016, Genomics data.
[29] Robert L. Tanguay,et al. Facility Design and Health Management Program at the Sinnhuber Aquatic Research Laboratory. , 2016, Zebrafish.
[30] Daniel J. Gaffney,et al. A survey of best practices for RNA-seq data analysis , 2016, Genome Biology.
[31] Eran Elinav,et al. Use of Metatranscriptomics in Microbiome Research , 2016, Bioinformatics and biology insights.
[32] Daniel Krewski,et al. Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals. , 2015, Regulatory toxicology and pharmacology : RTP.
[33] April Z. Gu,et al. Toxicity mechanisms identification via gene set enrichment analysis of time-series toxicogenomics data: impact of time and concentration. , 2015, Environmental science & technology.
[34] P. Moll,et al. QuantSeq 3′ mRNA sequencing for RNA quantification , 2014, Nature Methods.
[35] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[36] Paul Theodor Pyl,et al. HTSeq – A Python framework to work with high-throughput sequencing data , 2014, bioRxiv.
[37] Vineet Bafna,et al. Annotation of the Zebrafish Genome through an Integrated Transcriptomic and Proteomic Analysis , 2014, Molecular & Cellular Proteomics.
[38] T. Urich,et al. Metatranscriptomic Analysis of Arctic Peat Soil Microbiota , 2014, Applied and Environmental Microbiology.
[39] Joakim Lundeberg,et al. Sequencing Degraded RNA Addressed by 3' Tag Counting , 2014, PloS one.
[40] Aviv Regev,et al. Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples , 2013, Nature Methods.
[41] Paul Theodor Pyl,et al. The Genomic and Transcriptomic Landscape of a HeLa Cell Line , 2013, G3: Genes, Genomes, Genetics.
[42] G. Tyson,et al. Application of metatranscriptomics to soil environments. , 2012, Journal of microbiological methods.
[43] H. Binder,et al. Estimating RNA-quality using GeneChip microarrays , 2012, BMC Genomics.
[44] Steven L Salzberg,et al. Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.
[45] Mushfiqur R. Sarker,et al. Automated Zebrafish Chorion Removal and Single Embryo Placement , 2012, Journal of laboratory automation.
[46] H. Steven Wiley,et al. Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling , 2011, Bioinform..
[47] Eric T. Wang,et al. Analysis and design of RNA sequencing experiments for identifying isoform regulation , 2010, Nature Methods.
[48] Christian Schlötterer,et al. Gene expression profiling by massively parallel sequencing. , 2007, Genome research.
[49] Stanley N Cohen,et al. Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[50] C. Kimmel,et al. Stages of embryonic development of the zebrafish , 1995, Developmental dynamics : an official publication of the American Association of Anatomists.
[51] J. Bageritz,et al. Single-Cell RNA Sequencing with Drop-Seq. , 2019, Methods in molecular biology.
[52] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[53] M. Gerstein,et al. RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.