The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR
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Citations
Cites
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219
Self-citationMcCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
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
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Self-citationNCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy
Pruitt, K. D., Tatusova, T., Brown, G. R., & Maglott, D. R. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1079 · Cited by 1,149 · cited 1×
“By default, the function uses RefSeq annotation from the National Center for Biotechnology Information (NCBI) giving the start and end positions of each exon [19].”
MethodStein's Estimation Rule and its Competitors—An Empirical Bayes Approach
Efron, B., & Morris, C. (1973) · Journal of the American Statistical Association · doi:10.1080/01621459.1973.10481350 · Cited by 981
Moderated statistical tests for assessing differences in tag abundance
Robinson, M. D., & Smyth, G. K. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm453 · Cited by 856
Self-citation
Cited by
ComBat-seq: batch effect adjustment for RNA-seq count data
Zhang, Y., Parmigiani, G., & Johnson, W. E. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa078 · Cited by 1,566
Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
L. Lun, A. T., Bach, K., & Marioni, J. C. (2016) · Genome Biology · doi:10.1186/s13059-016-0947-7 · Cited by 1,108
Bias, robustness and scalability in single-cell differential expression analysis
Soneson, C., & Robinson, M. D. (2018) · Nature Methods · doi:10.1038/nmeth.4612 · Cited by 770
Dou, Y., Cha, D. J., Franklin, J. L., Higginbotham, J. N., Jeppesen, D. K., Weaver, A. M., Prasad, N., Levy, S., Coffey, R. J., Patton, J. G., et al. (2016) · Scientific Reports · doi:10.1038/srep37982 · Cited by 328
Molecular mechanisms underlying nuchal hump formation in dolphin cichlid, Cyrtocara moorii
Lecaudey, L. A., Sturmbauer, C., Singh, P., & Ahi, E. P. (2019) · Scientific Reports · doi:10.1038/s41598-019-56771-7 · Cited by 30
Metadata
- Authors
- Chen, Y., Lun, A. T. L., & Smyth, G. K.
- Venue
- Statistical Analysis of Next Generation Sequencing Data
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 51-74
- OpenAlex
- W54517741
- Cited by
- 171
- References
- 8
- FWCI
- 13.10
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Chen, Y., Lun, A. T. L., & Smyth, G. K. (2014). Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR. Statistical Analysis of Next Generation Sequencing Data. https://doi.org/10.1007/978-3-319-07212-8_3
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
