Statistical Design and Analysis of RNA Sequencing Data

Cited by (406)

Items 301–400 of 406

1. Mapping of Expression Quantitative Trait Loci Using RNA-seq Data
   Wei Sun, Yi‐Juan Hu · 2014 · Springer eBooks
2. Detecting bacterial genomes in a metagenomic sample using NGS reads
   Camilo Valdes, Meghan M. Brennan, Bertrand S. Clarke, Jennifer Clarke · 2015 · Statistics and Its Interface
3. The Platelet Transcriptome: Coding RNAs
   Jesse W. Rowley, Bhanu Kanth Manne, Andrew S. Weyrich · 2017 · Springer eBooks
4. Preparation of Vibrio cholerae Samples for RNA-seq Analysis
   Jyl S. Matson · 2018 · Methods in molecular biology
5. Diversity and Roles of Mycorrhizal Fungi in the Bee Orchid Ophrys apifera
   WR Abdullah · 2018 · University of Liverpool
6. Reverse Engineering Gene Networks Using Genomic Time-Course Data
   Andréa Rau, Hal Id Tel, Rebecca W. Doerge, Bruce Α. Craig, Florence Jaffrézic, Jayanta K. Ghosh, Yuan (alan Qi · 2010 · HAL
7. Retraction Note: Species-specific chemosensory gene expression in the olfactory organs of the malaria vector Anopheles gambiae
   Theresa K. Hodges, Luciano V. Cosme, Giridhar Athrey, Sharmila Pathikonda, Willem Takken, Michel A. Slotman · 2015 · BMC Genomics · Retracted
8. Identification of Arabidopsis genes involved in differential interaction phenotype establishment by distinct Verticillium spp. and isolates
   Dimitri Stepanets · 2018
9. Experimental design for large scale omic studies
   Funda Ogut, Jeremy R. B. Newman, Rhonda L. Bacher, PATRICK J. CONCANNON, Koen J. F. Verhoeven, Lauren M. McIntyre · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
10. Optimal balancing of clinical factors in large scale clinical RNA-Seq studies
    Austin W.T. Chiang, Vahid Gazestani, Mia G. Altieri, Benjamin P. Kellman, Srinivsa Nalabolu, Tiziano Pramparo, Karen Pierce, Eric Courchesne, Nathan E. Lewis · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
11. Role of Data Mining in Bioinformatics
    Vivek P. Chavda, Amit Sorathiya, Disha Valu, Swati Marwadi · 2021
12. Comparison of direct cDNA and PCR-cDNA Nanopore sequencing of Escherichia coli isolates
    Gillian Rodger, Samuel Lipworth, Lucinda K. Barrett, Sarah J Oakley, Derrick W. Crook, David W. Eyre, Nicole E Stoesser · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
13. Bioinformatics and Next- generation Sequencing
    Adam Krejčí, Petr Müller, Bořivoj Vojtěšek · 2015 · Klinicka onkologie
14. Influence of RNA‐Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation
    Ylenia Chiari, Leif Howard, Nickolas Moreno, Scott Relyea, James L. Dunnigan, Matthew C. Boyer, Marty D. Kardos, Scott R. Glaberman, Gordon Luikart · 2023 · Molecular Ecology Resources
15. Leveraging remeasured samples in biomedical studies
    Luer Zhong, Rhonda L. Bacher · 2023 · Nature Computational Science
16. Integration of bulk RNA-seq pipeline metrics for assessing low-quality samples
    Samuel Hamilton, Gaurav T. Gadhvi, Tyler Therron, Deborah R. Winter, SCRIPT Study Investigators · 2026 · BMC Bioinformatics
17. Pushing for the Extreme: Estimation of Poisson Distribution from Low Count Unreplicated Data—How Close Can We Get?
    Peter Tiňo B · 2013 · Entropy
18. Cotton promoters for controlled gene expression
    Ana Luiza Atella, Maria Fátima Grossi‐de‐Sá, Márcio Alves‐Ferreira · 2023 · Electronic Journal of Biotechnology
19. β‐Catenin in the kidney stroma modulates pathways and genes to regulate kidney development
    Erin Deacon, Anna Li, Felix J. Boivin, Anna Dvorkin‐Gheva, Joanna Cunanan, Darren J. Bridgewater · 2023 · Developmental Dynamics
20. Best practices for the ATAC-seq assay and its data analysis
    Haibo Liu, Rui Li, Kai Hu, Jianhong Ou, Magnolia L. Pak, Michael R. Green, Lihua Julie Zhu · 2024 · Elsevier eBooks
21. The Interplay of Ontogeny and Phylogeny at the Transcriptome Level of the Tetrapod Heart
    Gerardo A. Cordero, Alisha K. Holloway, T. Friedrich, John Eme, Walter L. Eckalbar, Kenro Kusumi, Fredric J. Janzen, James W. Hicks, Frank L. Conlon, Benoit G. Bruneau et al. · 2025 · Journal of Experimental Zoology Part B Molecular and Developmental Evolution
22. Gene Expression Analysis
    Cedric Gondro · 2015 · Use R!
23. RNA-Seq Data Analysis in Prokaryotes: A Review for Non-experts
    Andrés Eduardo Rodríguez Cubillos, Laura Perlaza-Jiménez, Adriana Jimena Bernal Giraldo · 2014 · Acta Biológica Colombiana
24. RNA-SEQ: A GLANCE AT TECHNOLOGIES AND METHODOLOGIES RNA-Seq: un vistazo sobre las tecnologías y metodologías
    Seyed Mehdi Jazayeri, Luz Marina, Melgarejo Muñoz, Hernán Mauricio Romero · 2015
25. Using Translating Ribosome Affinity Purification (TRAP) to Understand Cell-Specific Translatomes in Pain States
    Diana Tavares‐Ferreira, Salim Megat, Theodore John Price · 2022 · Neuromethods
26. The application and challenges of RNA-sequencing to the study of circadian rhythms
    Nicholas F. Lahens · 2014 · ScholarlyCommons (University of Pennsylvania)
27. Cancer Transcriptome Sequencing and Analysis
    Ryan D. Morin, Stephen B. Montgomery · 2013 · Elsevier eBooks
28. The Evolutionary Feedback between Genetic Conflict and Genome Architecture
    Adrian Young · 2014 · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
29. Suporte ao desenvolvimento e à composição de serviços web semânticos para a análise de expressão gênica
    Gabriela Der Agopian Guardia · 2016 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
30. Examination of the effect of weaning stress on the physiological and molecular regulation of immune function in circulating bovine leukocytes
    Aran O’Loughlin · 2011 · Maynooth University ePrints and eTheses Archive (Maynooth University)
31. Medical Devices
    Gregory Campbell, Heng Li, Gene A. Pennello, Lilly Q. Yue · 2018 · Wiley eBooks
32. Tau Ablation Rewires Brain Cell Programs in Health and Restores Function in Disease
    Chimal-Juárez, Enrique, Patel, Henika, Jury-Garfe, Nur, Dabin, Luke C., Vidal, Ruben, Kim, Jungsu, Lasagna-Reeves, Cristian A. · 2026 · bioRxiv
33. Pre- and post-natal stress programming: from genes to physiology
    Valeria Marasco · 2014 · Enlighten: Theses (The University of Glasgow)
34. Measurement, Summary, and Methodological Variation in RNA-sequencing
    Alyssa C. Frazee, Leonardo Collado Torres, Andrew E. Jaffe, Ben Langmead, Jeffrey T. Leek · 2014 · Springer eBooks
35. Transcriptomics Technology: Promise and Potential Pitfalls
    Can Bruce, Asli Uyar · 2013 · Springer eBooks
36. Time Course RNA-seq: A Potential Avenue with Somewhat Different Approach in Tandem of Differential Analysis
    Sunghee Oh, Hongyu Zhao, James P. Noonan · 2012 · ... International Conference on Complex, Intelligent and Software Intensive Systems
37. Statistical Analysis of Gene Expression and Genomic Data
    Marcos Deon Vilela de Resende, Fabyano Fonseca e Silva, Moysés Nascimento, Camila Ferreira Azevedo, Luíz Alexandre Peternelli · 2015 · Springer eBooks
38. RNA-Seq reveals differences in the global transcriptome between high- and low-
    Devendra H. Shah · 2013
39. Optimal block designs for experiments with responses drawn from a Poisson distribution
    Stephen Bush, Katya Ruggiero · 2016 · arXiv (Cornell University)
40. De novo RNA sequencing enables transcriptome studies in non-model species : gene expression patterns involved in Drosophila montana reproductive diapause
    Mikko Merisalo · 2014 · Jyväskylä University Digital Archive (University of Jyväskylä)
41. Padrão de expressão gênica na área do ligamento periodontal durante o desenvolvimento radicuar
    Ana Paula Oliveira Giorgetti Bossolan · 2013
42. iSeg: an algorithm for segmentation of genomic data
    Senthil Balaji Girimurugan, Jonathan H. Dennis, Jinfeng Zhang · 2015 · arXiv (Cornell University)
43. Holocene Legacy: Evolution of Thermal Tolerance and Bloodfeeding in the Pitcher-Plant Mosquito, Wyeomyia smithii
    Alida T. Gerritsen · 2014 · Scholars' Bank (University of Oregon)
44. Sociogenomics of social organization: mechanistic and evolutionary underpinnings of caste development and facial recognition in paper wasps
    Ali J. Berens · 2015 · Iowa State University Digital Repository (Iowa State University)
45. The identification of non-protein coding rna in the tumour vasculature
    Klarke M. Sample · 2016 · University of Birmingham Institutional Research Archive (University of Birmingham)
46. Analyse und Interpretation der Varianz von Genexpressionsdaten
    Christian Hummert · 2015 · Common Library Network (Der Gemeinsame Bibliotheksverbund)
47. Metagenomic Design and Sequencing
    William L. Trimble, Stephanie M. Greenwald, Sarah M. Owens, Elizabeth M. Glass, Folker Meyer · 2016 · Springer eBooks
48. Transcriptome Profiling Strategies
    Abdullah M. Khamis, Vladimir B. Bajić, Matthias Harbers · 2016 · Springer eBooks
49. Role of NFAT (Nuclear Factor of Activated T Cells)Transcription Factors in Hematopoiesis
    Laleh S. Arabanian · 2012
50. Measuring Gene Expression With Next Generation Sequencing Technology
    Michele Busby · 2012
51. Characterizing Immune Responses to Marburg Virus Infection in Animal Hosts Using Statistical Transcriptomic Analysis
    Albert Kim Lee · 2018
52. Análise do transcritoma de Haemophilus influenzae tipo b durante o processo de fermentação em biorreator
    Carlos Eduardo Madureira Trufen · 2018 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
53. Sample size calculations and normalization methods for RNA-seq data.
    Xiaohong Li · 2017
54. Analysis of expression profile and gene variation via development of methods for Next Generation Sequencing data
    Alexander Wolff · 2018 · eDiss (Georg-August-Universität Göttingen)
55. Mining disease resistance genes in cassava using next-generation sequencing
    Gerald Otti · 2016 · Greenwich Academic Literature Archive (University of Greenwich)
56. Análise do transcriptoma (RNAseq) das células foliculares tireoidianas revela uma diversidade de ações autócrinas do T3.
    Rafael Benjamin Araújo Dias · 2019
57. Genetic and cellular mechanisms of autoimmunity in lupus-prone B6.129-Sle16 mice
    Norzawani B Buang · 2017 · Spiral (Imperial College London)
58. Diagnosis of Mendelian Inherited Disorders in Dogs: Brief Literature Review
    Vlad Cocostîrc, Dana Liana PUSTA · 2020 · Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Veterinary Medicine
59. Differential Expression From Microarray and RNA-seq Experiments
    Marc Delord · 2018 · Elsevier eBooks
60. Gene expression estimates: Influence of sequencing library construction, fish sampling methods, and tissue harvesting time
    Nickolas Moreno, L. B. Howard, Scott Relyea, James L. Dunnigan, Matthew Boyer, Marty D. Kardos, Scott R. Glaberman, Gordon Luikart, Ylenia Chiari · 2021
61. Faculty Opinions recommendation of RNA-seq differential expression studies: more sequence or more replication?
    Chris H. Raine · 2014 · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
62. References
    2016 · CRC Press eBooks
63. The Bench Scientist’s Guide to Statistical Analysis of RNA-Seq Data
    Craig R. Yendrek, Elizabeth A. Ainsworth, Jyothi Thimmapuram · 2014 · Apple Academic Press eBooks
64. Faculty Opinions recommendation of Translatome regulation in neuronal injury and axon regrowth.
    Phillip G. Popovich · 2019 · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
65. Comprehensive Analysis of Differences of N6-Methyladenosine of Lncrnas Between Atrazine-Inducedand Normal Xenopus Laevis Testis
    Xue‐Jie Qi, Geng Xiao, Juan Zhang, Ling Li, Qiang Jia, Binpeng Qu, Wenhui Yin, Qiming Guo, Cunxiang Bo, Linlin Sai et al. · 2021
66. Peer Review #3 of "Getting the most out of RNA-seq data analysis (v0.1)"
    2015 · PeerJ
67. Peer Review #1 of "Getting the most out of RNA-seq data analysis (v0.2)"
    2015 · PeerJ
68. Designing Experiments for Sound Statistical Inference
    Melissa Key, Olga Vitek A · 2013 · Springer eBooks
69. Peer Review #2 of "Getting the most out of RNA-seq data analysis (v0.1)"
    2015 · PeerJ
70. Peer Review #2 of "Getting the most out of RNA-seq data analysis (v0.2)"
    2015 · PeerJ
71. Peer Review #3 of "Getting the most out of RNA-seq data analysis (v0.2)"
    2015 · PeerJ
72. Peer Review #1 of "Getting the most out of RNA-seq data analysis (v0.1)"
    2015 · PeerJ
73. A Review on Bioinformatics Tools for Transcriptomics NGS Data Analysis
    2022 · Letters in Applied NanoBioScience
74. An alternative derivation of weak convergence concerning quasi-likelihood estimation with a small-sample correction for simultaneous testing
    Bo Li · 2023 · Journal of Statistical Computation and Simulation
75. Desenvolvimento floral em maracujazeiro
    Mariana Bombardi da Silva · 2022
76. Transcriptomic profiling–based identification of biomarkers of stem cells
    Swati Sharma, Daizy Kalpdev, Ankit Choudhary · 2024 · Elsevier eBooks
77. Machine Learning Based Cancer Classification Using Gene Expression Data
    Ruiyi Li · 2024 · International Journal of Machine Learning
78. Selective testing and its effect on false discovery rate controlling procedures under discrete framework
    Aniket Biswas, Abhik Sinha · 2024 · Communications in Statistics - Simulation and Computation
79. Variation in bulk RNA-seq and estimated cell type proportion using deconvolution when comparing pancreatic cancer samples within the same individual
    Rick J. Jansen, Sarah A. Munro, Samuel O. Antwi, Kari G. Rabe, Hugues Sicotte · 2025 · medRxiv
80. Telmisartan modulates exercise responses in peripheral artery disease: Analyses of skeletal muscle from the TELEX Trial
    Kate Kosmac, Jai Kumar Joshi, Mary McGrae McDermott, Jada C. Stewart, Dongxue Zhang, Shujun Xu, Karen J. Ho, Robert L. Sufit, Luigi Ferrucci, Charlotte A. Peterson et al. · 2025 · JVS Vascular Science
81. Platelets as Carriers for Antitumor Therapy
    Christopher J. Bethel, Marco Malvestiti · 2025 · Springer eBooks
82. Bulk RNA-seq deconvolution heterogeneity across paired pancreatic cancer human samples
    Rick J. Jansen, Sarah A. Munro, Samuel O. Antwi, Kari G. Rabe, Hugues Sicotte · 2025 · Frontiers in Genetics
83. Additional file 1 of On the utility of RNA sample pooling to optimize cost and statistical power in RNA sequencing experiments
    Takele Assefa, Alemu, Vandesompele, Jo, Olivier Thas · 2020 · Figshare
84. Additional file 1 of Comprehensive analysis of differences of N6-methyladenosine of lncRNAs between atrazine-induced and normal Xenopus laevis testis
    Qi, Xuejie, Geng, Xiao, Zhang, Juan, Binpeng Qu, Zhang, Xin, Jia, Qiang, Wenhui Yin, Cunxiang Bo, Liu, Yan, Li, Hao et al. · 2021 · Figshare
85. Additional file 4 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
86. Additional file 2 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Andrade-Navarro, Miguel A., Fontaine, Jean-Fred · 2024 · Figshare
87. Additional file 6 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
88. Additional file 14 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
89. Additional file 10 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
90. Additional file 15 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
91. Additional file 8 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
92. Additional file 9 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
93. Additional file 13 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
94. Additional file 11 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
95. Additional file 1 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
96. Additional file 3 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
97. Additional file 5 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
98. Additional file 7 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
99. Additional file 12 of Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets
    Sprang, Maximilian, Jannik S. Möllmann, Miguel Angel Andrade-Navarro, Fontaine, Jean-Fred · 2024 · Figshare
100. Microgravity effects on secondary metabolism of plant-affecting bacteria
     Gayatri Sharma, MH Ahmed, Tahir Ali, Paul D. Boudreau, Patrick D. Curtis · 2026 · Microbiology Spectrum