NanoStringDiff: A novel statistical method for differential expression analysis based on NanoString nCounter data

Nucleic Acids Research

Volumn 44, Issue 20, 2016, Pages e151-

  Wang, Hong ^a   Horbinski, Craig ^b   Wu, Hao ^c   Liu, Yinxing ^d   Sheng, Shaoyi ^e   Liu, Jinpeng ^f   Weiss, Heidi ^a,f   Stromberg, Arnold J ^a   Wang, Chi ^a,f  

^a UNIVERSITY OF KENTUCKY   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

^c EMORY UNIVERSITY   (United States)

^d UNIVERSITY OF KENTUCKY   (United States)

^e Paul Laurence Dunbar High School   (United States)

^f UNIVERSITY OF KENTUCKY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; DATA PROCESSING; DIFFERENTIALLY EXPRESSED GENE; GENE EXPRESSION; HOUSEKEEPING GENE; INTERMETHOD COMPARISON; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; ALGORITHM; BIOLOGY; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; INFORMATION PROCESSING; PROCEDURES; REPRODUCIBILITY;

MESSENGER RNA; MICRORNA;

ALGORITHMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATASETS AS TOPIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MICRORNAS; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; RNA, MESSENGER;

EID: 85016102098     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkw677     Document Type: Article

References (29)

1. Geiss,G.K., Bumgarner,R.E., Birditt,B., Dahl,T., Dowidar,N., Dunaway,D.L., Fell,H.P., Ferree,S., George,R.D., Grogan,T. et al. (2008) Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat. Biotechnol., 26, 317-325.
2. Reis,P.P., Waldron,L., Goswami,R.S., Xu,W., Xuan,Y., Perez-Ordonez,B., Gullane,P., Irish,J., Jurisica,I. and Kamel-Reid,S. (2011) mRNA transcript quantification in archival samples using multiplexed, color-coded probes. BMC Biotechnol., 11, 46.
3. Waggott,D., Chu,K., Yin,S., Wouters,B.G., Liu,F.-F. and Boutros,P.C. (2012) NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data. Bioinformatics, 28, 1546-1548.
4. Brumbaugh,C.D., Kim,H.J., Giovacchini,M. and Pourmand,N. (2011) NanoStriDE: normalization and differential expression analysis of NanoString nCounter data. BMC Bioinformatics, 12, 479.
5. Anders,S. and Huber,W. (2010) Differential expression analysis for sequence count data. Genome Biol., 11, R106.
6. Robinson,M.D. and Smyth,G.K. (2007) Moderated statistical tests for assessing differences in tag abundance. Bioinformatics, 23, 2881-2887.
7. Robinson,M.D. and Smyth,G.K. (2008) Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics, 9, 321-332.
8. Robinson,M.D., McCarthy,D.J. and Smyth,G.K. (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26, 139-140.
9. Hardcastle,T.J. and Kelly,K.A. (2010) baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics, 11, 422.
10. Wu,H., Wang,C. and Wu,Z. (2013) A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data. Biostatistics, 14, 232-243.
11. Benjamini,Y. and Hochberg,Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B, 57, 289-300.
12. Mori,M., Triboulet,R., Mohseni,M., Schlegelmilch,K., Shrestha,K., Camargo,F.D. and Gregory,R.I. (2014) Hippo signaling regulates microprocessor and links cell-density-dependent miRNA biogenesis to cancer. Cell, 156, 893-906.
13. Busskamp,V., Lewis,N.E., Guye,P., Ng,A.H., Shipman,S.L., Byrne,S.M., Sanjana,N.E., Murn,J., Li,Y., Li,S. et al. (2014) Rapid neurogenesis through transcriptional activation in human stem cells. Mol. Syst. biol., 10, 760.
14. Teruel-Montoya,R., Kong,X., Abraham,S., Ma,L., Kunapuli,S.P., Holinstat,M., Shaw,C.A., McKenzie,S.E., Edelstein,L.C. and Bray,P.F. (2014) MicroRNA expression differences in human hematopoietic cell lineages enable regulated transgene expression. PLoS One, 9, e102259.
15. Love,M.I., Huber,W. and Anders,S. (2014) Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol., 15, 550.
16. Agrawal,R., Pandey,P., Jha,P., Dwivedi,V., Sarkar,C. and Kulshreshtha,R. (2014) Hypoxic signature of microRNAs in glioblastoma: insights from small RNA deep sequencing. BMC Genomics, 15, 686.
17. Slattery,M.L., Herrick,J.S., Mullany,L.E., Valeri,N., Stevens,J., Caan,B.J., Samowitz,W. and Wolff,R.K. (2015) An evaluation and replication of miRNAs with disease stage and colorectal cancer-specific mortality. Int. J. Cancer, 137, 428-438.
18. Sun,E., Zhou,Q., Liu,K., Wei,W., Wang,C., Liu,X., Lu,C. and Ma,D. (2014) Screening miRNAs related to different subtypes of breast cancer with miRNAs microarray. Eur. Rev. Med. Pharmacol. Sci., 18, 2783-2788.
19. Xie,J., Tan,Z.-H., Tang,X., Mo,M.-S., Liu,Y.-P., Gan,R.-L., Li,Y., Zhang,L. and Li,G.-Q. (2014) miR-374b-5p suppresses RECK expression and promotes gastric cancer cell invasion and metastasis. World J. Gastroenterol., 20, 17439-17447.
20. Ouyang,M., Li,Y., Ye,S., Ma,J., Lu,L., Lv,W., Chang,G., Li,X., Li,Q., Wang,S. et al. (2014) MicroRNA profiling implies new markers of chemoresistance of triple-negative breast cancer. PLoS One, 9, e96228.
21. Chen,G., Shen,Z.-L., Wang,L., Lv,C.-Y., Huang,X.-E. and Zhou,R.-P. (2013) Hsa-miR-181a-5p expression and effects on cell proliferation in gastric cancer. Asian Pac. J. Cancer Prev., 14, 3871-3875.
22. Wang,Z., Bao,Z., Yan,W., You,G., Wang,Y., Li,X. and Zhang,W. (2013) Isocitrate dehydrogenase 1 (IDH1) mutation-specific microRNA signature predicts favorable prognosis in glioblastoma patients with IDH1 wild type. J. Exp. Clin. Cancer Res., 32, 59.
23. Zhang,C., Zhang,J., Hao,J., Shi,Z., Wang,Y., Han,L., Yu,S., You,Y., Jiang,T., Wang,J. et al. (2012) High level of miR-221/222 confers increased cell invasion and poor prognosis in glioma. J. Transl. Med., 10, 1-11.
24. Yang,F., Wang,W., Zhou,C., Xi,W., Yuan,L., Chen,X., Li,Y., Yang,A., Zhang,J. and Wang,T. (2015) MiR-221/222 promote human glioma cell invasion and angiogenesis by targeting TIMP2. Tumor Biol., 36, 3763-3773.
25. Tao,K., Yang,J., Guo,Z., Hu,Y., Sheng,H., Gao,H. and Yu,H. (2014) Prognostic value of miR-221-3p, miR-342-3p and miR-491-5p expression in colon cancer. Am. J. Transl. Res., 6, 391-401.
26. Ma,J., Yao,Y., Wang,P., Liu,Y., Zhao,L., Li,Z., Li,Z. and Xue,Y. (2014) MiR-152 functions as a tumor suppressor in glioblastoma stem cells by targeting Krüppel-like factor 4. Cancer Lett., 355, 85-95.
27. Yao,Y., Ma,J., Xue,Y., Wang,P., Li,Z., Liu,J., Chen,L., Xi,Z., Teng,H., Wang,Z. et al. (2015) Knockdown of long non-coding RNA XIST exerts tumor-suppressive functions in human glioblastoma stem cells by up-regulating miR-152. Cancer Lett., 359, 75-86.
28. Zheng,X., Chopp,M., Lu,Y., Buller,B. and Jiang,F. (2013) MiR-15b and miR-152 reduce glioma cell invasion and angiogenesis via NRP-2 and MMP-3. Cancer Lett., 329, 146-154.
29. Xu,S., Wei,J., Wang,F., Kong,L.-Y., Ling,X.-Y., Nduom,E., Gabrusiewicz,K., Doucette,T., Yang,Y., Yaghi,N.K. et al. (2014) Effect of miR-142-3p on the M2 macrophage and therapeutic efficacy against murine glioblastoma. J. Natl. Cancer Inst., 106, dju162.