The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples
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Citations
Cites
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
RNA sequencing: advances, challenges and opportunities
Ozsolak, F., & Milos, P. M. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2934 · Cited by 2,135 · cited 1×
“There are various approaches to solve that problem (Jiang and Wong 2009; Wang et al. 2009; Ozsolak and Milos 2011).”
Background
Cited by
Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences
Soneson, C., Love, M. I., & Robinson, M. D. (2015) · F1000Research · doi:10.12688/f1000research.7563.1 · Cited by 3,929
Finucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., Gazal, S., Loh, P.-R., Lareau, C., Shoresh, N., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0081-4 · Cited by 1,097
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
Haque, A., Engel, J., Teichmann, S. A., & Lönnberg, T. (2017) · Genome Medicine · doi:10.1186/s13073-017-0467-4 · Cited by 1,071
Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression
Schmiedel, B. J., Singh, D., Madrigal, A., Valdovino-Gonzalez, A. G., White, B. M., Zapardiel-Gonzalo, J., Ha, B., Altay, G., Greenbaum, J. A., McVicker, G., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.022 · Cited by 867
Zeng, D., Li, M., Zhou, R., Zhang, J., Sun, H., Shi, M., Bin, J., Liao, Y., Rao, J., & Liao, W. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0436 · Cited by 986
“For TCGA dataset, RNA-sequencing data (FPKM values) were transformed into transcripts per kilobase million (TPM) values, which are more similar to those resulting from microarrays and more comparable between samples (24).”
Method
Metadata
- Authors
- Wagner, G. P., Kin, K., & Lynch, V. J.
- Venue
- Theory in Biosciences
- Published
- 2012-08-08
- Volume
- 131
- Issue
- 4
- Pages
- 281-285
- ISSN
- 1431-7613 (ISSN-L)
- 1611-7530
- OpenAlex
- W1966116114
- Cited by
- 2,136
- References
- 3
- FWCI
- 11.27
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. https://app.cochat.ai/papers/10.1007/s12064-012-0162-3
- The paper
- Wagner, G. P., Kin, K., & Lynch, V. J. (2012). Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory in Biosciences. https://doi.org/10.1007/s12064-012-0162-3
Data sources
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.