Sequencing technology does not eliminate biological variability

Mapping and quantifying mammalian transcriptomes by RNA-Seq

Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696

RNA-Seq: a revolutionary tool for transcriptomics

Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring

Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., et al. (1999) · Science · doi:10.1126/science.286.5439.531 · Cited by 11,516

Stochastic Gene Expression in a Single Cell

Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441

Alternative isoform regulation in human tissue transcriptomes

Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research · doi:10.1101/gr.079558.108 · Cited by 2,771

Tackling the widespread and critical impact of batch effects in high-throughput data

Leek, J. T., Scharpf, R. B., Bravo, H. C., Simcha, D., Langmead, B., Johnson, W. E., Geman, D., Baggerly, K., & Irizarry, R. A. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2825 · Cited by 2,196

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

MAQC Consortium, Shi, L., Shi, L., Reid, L. H., Jones, W. D., Shippy, R., Warrington, J. A., Baker, S. C., Collins, P. J., de Longueville, F., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1239 · Cited by 2,126

Relative Impact of Nucleotide and Copy Number Variation on Gene Expression Phenotypes

Stranger, B. E., Forrest, M. S., Dunning, M., Ingle, C., Beazley, C., Thorne, N., Redon, R., Bird, C., Grassi, A., Lee, C., et al. (2007) · Science · doi:10.1126/science.1136678 · Cited by 1,743

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

Bullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-94 · Cited by 1,680

The effects of food rationing on phenotypic plasticity in reproductive resource allocation in female wild-type zebrafish, Danio rerio

Holmes, H. A. C. (2020) · Otago University Research Archive (University of Otago)

Gene expression estimates: Influence of sequencing library construction, fish sampling methods, and tissue harvesting timePreprint

Moreno, N., Howard, L. B., Relyea, S., Dunnigan, J. L., Boyer, M., Kardos, M. D., Glaberman, S. R., Luikart, G., & Chiari, Y. (2021) · doi:10.22541/au.161142130.04599849/v1

TVScript: A Tool for Exploring the Effects of Intra-Condition Variation on the Detection of Differentially Expressed GenesPreprint

Lobo, D., Godinho, R., & Archer, J. P. (2021) · Research Square · doi:10.21203/rs.3.rs-468506/v1

Taming of the wild: a new method for cross study RNA-seq analysisPreprint

Lobo, D., Godinho, R., & Archer, J. P. (2020) · doi:10.21203/rs.3.rs-27674/v1

Faculty Opinions recommendation of RNA-seq differential expression studies: more sequence or more replication?

Raine, C. H. (2014) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.718201663.793491281

Policy Corner

Morrell, M. J. (2013) · Physiology News · doi:10.36866/pn.90.9

Editorial

Collis, M. (2013) · Physiology News · doi:10.36866/pn.90.5

Transcriptome Analysis of Artificial Cultivated Mushrooms in Qinba MountainsPreprint

Li, Z., Haixia, M. A., Tan, J., Zhao, Y., Huang, J., & Yue, T. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4131992

Differentiation in Medical Practise using Sophisticated Data Analytics

Bhagat, A. K., & Chauhan, A. (2023) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite57410.2023.10182429

Rigor and reproducibility of RNA sequencing analyses

Buschmann, D., Driedonks, T. A. P., Huang, Y., Tosar, J. P., Turchinovich, A. A., & Witwer, K. W. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-817218-6.00009-7

Additional file 1 of Study on the differences of gene expression between pear and apple wild cultivation materials based on RNA-seq technique

Zhang, H., Li, M., Kong, M., Dunwell, J. M., Zhang, Y., Yue, C., Wu, J., & Zhang, S. (2021) · Figshare · doi:10.6084/m9.figshare.14737149

Additional file 2 of Study on the differences of gene expression between pear and apple wild cultivation materials based on RNA-seq technique

Zhang, H., Li, M., Kong, M., Dunwell, J. M., Zhang, Y., Yue, C., Wu, J., & Zhang, S. (2021) · Figshare · doi:10.6084/m9.figshare.14737152

Statistical methods for the analysis of complex epidemiology data

Acebes, M. E. (2023) · UPCommons institutional repository (Universitat Politècnica de Catalunya) · doi:10.5821/dissertation-2117-407878

Transcriptional profiling of the hippocampus and hypothalamus reveals a potential role of thyroid hormone in gamma-aminobutyric acid (GABA) synthesis in dairy cows fed a high-concentrate diet

Hou, M., Wu, C., Chen, Q., Song, P., Mao, S., & Ni, Y. (2025) · BMC Veterinary Research · doi:10.1186/s12917-025-05078-z

Additional file 3 of Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data

Wilfinger, W. W., Miller, R., Eghbalnia, H. R., Mackey, K., & Chomczyński, P. (2021) · Figshare · doi:10.6084/m9.figshare.14532353

Additional file 1 of High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

Cui, W., Xue, H., Wei, L., Jin, J., Tian, X., & Wang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13663221

Additional file 7 of Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data

Wilfinger, W. W., Miller, R., Eghbalnia, H. R., Mackey, K., & Chomczyński, P. (2021) · Figshare · doi:10.6084/m9.figshare.14532365

Additional file 1 of Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data

Chen, A., Kammers, K., Larman, H. B., Scharpf, R. B., & Ruczinski, I. (2022) · Figshare · doi:10.6084/m9.figshare.21130049

Additional file 1 of Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data

Wilfinger, W. W., Miller, R., Eghbalnia, H. R., Mackey, K., & Chomczyński, P. (2021) · Figshare · doi:10.6084/m9.figshare.14532347

Additional file 4 of High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

Cui, W., Xue, H., Wei, L., Jin, J., Tian, X., & Wang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13663233

Placental malaria is associated with a TLR–Endothelin-3–oxidative damage response in human placenta tissuesPreprint

Chenge, S., Mbalitsi, M., Ngure, H., Obimbo, M., Singoei, M., Kangogo, M., Kanoi, B. N., Gitaka, J., & Kobia, F. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.17.589949

Additional file 5 of Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data

Wilfinger, W. W., Miller, R., Eghbalnia, H. R., Mackey, K., & Chomczyński, P. (2021) · Figshare · doi:10.6084/m9.figshare.14532359

Additional file 5 of High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

Cui, W., Xue, H., Wei, L., Jin, J., Tian, X., & Wang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13663236

Additional file 3 of Study on the differences of gene expression between pear and apple wild cultivation materials based on RNA-seq technique

Zhang, H., Li, M., Kong, M., Dunwell, J. M., Zhang, Y., Yue, C., Wu, J., & Zhang, S. (2021) · Figshare · doi:10.6084/m9.figshare.14737155

Additional file 3 of High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

Cui, W., Xue, H., Wei, L., Jin, J., Tian, X., & Wang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13663230

Additional file 2 of High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

Cui, W., Xue, H., Wei, L., Jin, J., Tian, X., & Wang, Q. (2021) · Figshare · doi:10.6084/m9.figshare.13663224

Exploring Structure–Function Relationship of Lignin Derivatives to Enhance Its Biostimulant Potential

Shi, R., Wu, D., Manan, S., Rahman, M. M., Zhang, C., Wu, W., Jiang, B., & Jin, Y. (2026) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.5c12293

Comprehensive and bias-aware analysis of small RNA NGS data for biomarker detection with caRNAge

Kirchner, B., Grätz, C., Kersting, J., Schuster, M., Reithmair, M., List, M., & Pfaffl, M. W. (2026) · Extracellular Vesicles and Circulating Nucleic Acids · doi:10.20517/evcna.2026.78

Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data

Chen, A., Kammers, K., Larman, H. B., Scharpf, R. B., & Ruczinski, I. (2022) · BMC Genomics · doi:10.1186/s12864-022-08869-y · Cited by 14

Antibody reproducibility challenges: the solution lies in the sequence

Bradbury, A. M., Begley, G., Blow, N. S., Quarmby, V. E., Rimm, D. L., Burton, D., Lund‐Johansen, F., Montelione, G. T., Kossiakff, A., Wells, J. M., et al. (2016) · Nature · Cited by 1

Additional file 1 of Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data

Chen, A., Kammers, K., Larman, H. B., Scharpf, R. B., & Ruczinski, I. (2022) · Figshare · doi:10.6084/m9.figshare.21130049

Additional file 12 of RNA-seq: technical variability and sampling

McIntyre, L. M., Lopiano, K. K., Morse, A. M., Amin, V., Oberg, A. L., Young, L. J., & Nuzhdin, S. V. (2020) · Figshare · doi:10.6084/m9.figshare.12873233

Additional file 15 of RNA-seq: technical variability and sampling

McIntyre, L. M., Lopiano, K. K., Morse, A. M., Amin, V., Oberg, A. L., Young, L. J., & Nuzhdin, S. V. (2020) · Figshare · doi:10.6084/m9.figshare.12873242