SigFuge: Single gene clustering of RNA-seq reveals differential isoform usage among cancer samples

Nucleic Acids Research

Volumn 42, Issue 14, 2014, Pages

  Kimes, Patrick K ^a   Cabanski, Christopher R ^a,b   Wilkerson, Matthew D ^c,d   Zhao, Ni ^e   Johnson, Amy R ^f   Perou, Charles M ^c,d   Makowski, Liza ^c,f   Maher, Christopher A ^b   Liu, Yufeng ^a,c,f   Marron, J S ^a,c,f   Hayes, D Neil ^c,d  

^a The University of North Carolina at Chapel Hill   (United States)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF NORTH CAROLINA   (United States)

^d UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^e USA   (United States)

^f University of North Carolina at Chapel Hill   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATIVE RNA SPLICING; AREA UNDER THE CURVE; ARTICLE; BIOINFORMATICS; CDK2A GENE; CLINICAL EFFECTIVENESS; COHORT ANALYSIS; CONTROLLED STUDY; DATA ANALYSIS; DATA ANALYSIS SOFTWARE; DIAGNOSTIC TEST ACCURACY STUDY; FALSE POSITIVE RESULT; FAM64A GENE; GENE CLUSTER; GENE EXPRESSION PROFILING; GENE EXPRESSION SYSTEM; GENE IDENTIFICATION; GENE INACTIVATION; GENE LOCUS; GENE MAPPING; GENETIC ALGORITHM; GENETIC MARKER; GENETIC SCREENING; GENETIC TRANSCRIPTION; GENETIC VARIABILITY; GENOME ANALYSIS; GENOMICS; HEAD AND NECK SQUAMOUS CELL CARCINOMA; HIGH THROUGHPUT SCREENING; HIGH THROUGHPUT SEQUENCING; HUMAN; INTERMETHOD COMPARISON; KLK12 GENE; LUNG SQUAMOUS CELL CARCINOMA; MALIGNANT NEOPLASTIC DISEASE; PERFORMANCE MEASUREMENT SYSTEM; PRIORITY JOURNAL; PROCESS CONTROL; PROCESS DESIGN; PROCESS DEVELOPMENT; PROCESS MODEL; PROCESS MONITORING; PROCESS TECHNOLOGY; RECEIVER OPERATING CHARACTERISTIC; RNA SEQUENCE; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; TUMOR GENE; TUMOR SUPPRESSOR GENE;

ALTERNATIVE SPLICING; CARCINOMA, SQUAMOUS CELL; CARRIER PROTEINS; CLUSTER ANALYSIS; EXONS; GENE EXPRESSION PROFILING; GENES, P16; GENETIC LOCI; HEAD AND NECK NEOPLASMS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; KALLIKREINS; LUNG NEOPLASMS; NEOPLASMS; RNA ISOFORMS; SEQUENCE ANALYSIS, RNA; SOFTWARE;

EID: 84906227150     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku521     Document Type: Article

References (43)

1. Marioni, J.C., Mason, C.E., Mane, S.M., Stephens, M. and Gilad, Y. (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res., 18, 1509-1517.
2. Sultan, M., Schulz, M.H., Richard, H., Magen, A., Klingenhoff, A., Scherf, M., Seifert, M., Borodina, T., Soldatov, A., Parkhomchuk, D. et al. (2008) A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 321, 956-960.
3. Ramsköld, D., Wang, E.T., Burge, C.B. and Sandberg, R. (2009) An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput. Biol., 5, e1000598.
4. Maher, C.A., Kumar-Sinha, C., Cao, X., Kalyana-Sundaram, S., Han, B., Jing, X., Sam, L., Barrette, T., Palanisamy, N. and Chinnaiyan, A.M. (2009) Transcriptome sequencing to detect gene fusions in cancer. Nature, 458, 97-101.
5. Eisen, M.B., Spellman, P.T., Brown, P.O. and Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. U.S.A., 95, 14863-14868.
6. Perou, C., Sørlie, T., Eisen, M.B., van de Rijn, M., Jeffrey, S.S., Rees, C.A., Pollack, J.R., Ross, D.T., Johnsen, H., Akslen, L.A. et al. (2000) Molecular portraits of human breast tumours. Nature, 406, 747-752.
7. Hayes, D.N., Monti, S., Parmigiani, G., Gilks, C.B., Naoki, K., Bhattacharjee, A., Socinski, M.A., Perou, C.M. and Meyerson, M. (2006) Gene expression profiling reveals reproducible human lung adenocarcinoma subtypes in multiple independent patient cohorts. J. Clin. Oncol., 24, 5079-5090.
8. Maniatis, T. and Tasic, B. (2002) Alternative pre-mRNA splicing and proteome expansion in metazoans. Nature, 418, 236-243.
9. Wang, G.S. and Cooper, T.A. (2007) Splicing in disease: disruption of the splicing code and the decoding machinery. Nat. Rev. Genet., 8, 749-761.
10. Pan, Q., Shai, O., Lee, L.J., Frey, B.J. and Blencowe, B.J. (2008) Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat. Genet., 40, 1413-1415.
11. Trapnell, C., Hendrickson, D.G., Sauvageau, M., Goff, L., Rinn, J.L. and Pachter, L. (2013) Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat. Biotechnol., 31, 46-53.
12. Anders, S., Reyes, A. and Huber, W. (2012) Detecting differential usage of exons from RNA-seq data. Genome Res., 22, 2008-2017.
13. Hu, Y., Huang, Y., Du, Y., Orellana, C.F., Singh, D., Johnson, A.R., Monroy, A., Kuan, P.F., Hammond, S.M., Makowski, L. et al. (2013) DiffSplice: the genome-wide detection of differential splicing events with RNA-seq. Nucleic Acids Res., 41, e39.
14. Xi, L., Feber, A., Gupta, V., Wu, M., Bergemann, A.D., Landreneau, R.J., Litle, V.R., Pennathur, A., Luketich, J.D. and Godfrey, T.E. (2008) Whole genome exon arrays identify differential expression of alternatively spliced, cancer-related genes in lung cancer. Nucleic Acids Res., 36, 6535-6547.
15. Witten, D.M. (2011) Classification and clustering of sequencing data using a Poisson model. Ann. Appl. Stat., 5, 2493-2518.
16. Tong, P., Chen, Y., Su, X. and Coombes, K.R. (2013) SIBER: systematic identification of bimodally expressed genes using RNAseq data. Bioinformatics, 29, 605-613.
17. Klambauer, G., Unterthiner, T. and Hochreiter, S. (2013) DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions. Nucleic Acids Res., 41, e198.
18. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and 1000 Genome Project Data Processing Subgroup (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25, 2078-2079.
19. Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. and Wold, B. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods, 5, 621-628.
20. Bullard, J.H., Purdom, E., Hansen, K.D. and Dudoit, S. (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics, 11, 94.
21. Robinson, M.D. and Oshlack, A. (2010) A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol., 11:R25.
22. MacQueen, J. (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. University of California Press, Berkeley, California, Vol. 1, pp. 281-297.
23. Jolliffe, I.T. (2002) Principal Component Analysis. Springer, New York, NY.
24. Liu, Y., Hayes, D.N., Nobel, A.B. and Marron, J.S. (2008) Statistical significance of clustering for high-dimension, low-sample size data. J. Am. Stat. Assoc., 103, 1281-1293.
25. 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.
26. Pruitt, K.D., Tatusova, T., Klimke, W. and Maglott, D. (2009) NCBI Reference Sequences: current status, policy and new initiatives. Nucleic Acids Res., 37, D32-D36.
27. 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.
28. Blekhman, R., Marioni, J.C., Zumbo, P., Stephens, M. and Gilad, Y. (2010) Sex-specific and lineage-specific alternative splicing in primates. Genome Res., 20, 180-189.
29. The Cancer Genome Atlas Research Network. (2012) Comprehensive genomic characterization of squamous cell lung cancers. Nature, 489, 519-525.
30. Talieri, M., Devetzi, M., Scorilas, A., Pappa, E., Tsapralis, N., Missitzis, I. and Ardavanis, A. (2012) Human kallikrein-related peptidase 12 (KLK12) splice variants expression in breast cancer and their clinical impact. Tumor Biol., 33, 1075-1084.
31. Powers, D.M. (2011) Evaluation: from precision, recall and F-measure to ROC, informedness, markedness & correlation. J. Mach. Learn. Technol., 2, 37-63.
32. Cabanski, C.R., Wilkerson, M.D., Soloway, M., Parker, J.S., Liu, J., Prins, J.F., Marron, J.S., Perou, C.M. and Hayes, D.N. (2013) BlackOPs: increasing confidence in variant detection through mappability filtering. Nucleic Acids Res., 41, e178.
33. Archangelo, L.F., Greif, P.A., Hölzel, M., Harasim, T., Kremmer, E., Przemeck, G.K., Eick, D., Deshpande, A.J., Buske, C., de Angelis, M.H. et al. (2008) The CALM and CALM/AF10 interactor CATS is a marker for proliferation. Mol. Oncol., 2, 356-367.
34. Archangelo, L.F., Gläsner, J., Krause, A. and Bohlander, S.K. (2006) The novel CALM interactor CATS influences the subcellular localization of the leukemogenic fusion protein CALM/AF10. Oncogene, 25, 4099-4109.
35. Coulombe-Huntington, J., Lam, K.C., Dias, C. and Majewski, J. (2009) Fine-scale variation and genetic determinants of alternative splicing across individuals. PLoS Genet., 5, e1000766.
36. Dong, Y., Kaushal, A. and Brattsand, M. (2003) Differential splicing of KLK5 and KLK7 in epithelial ovarian cancer produces novel variants with potential as cancer biomarkers. Clin. Cancer Res., 9, 1710-1720.
37. Dong, Y., Bui, L.T., Odorico, D.M., Tan, O.L., Myers, S.A., Samaratunga, H., Gardiner, R.A. and Clements, J.A. (2005) Compartmentalized expression of kallikrein 4 (KLK4/hK4) isoforms in prostate cancer: nuclear, cytoplasmic and secreted forms. Endocr. Relat. Cancer, 12, 875-889.
38. Planque, C., Choi, Y.H., Guyetant, S., Heuzé-Vourc'h, N., Briollais, L. and Courty, Y. (2010) Alternative splicing variant of kallikrein-related peptidase 8 as an independent predictor of unfavorable prognosis in lung cancer. Clin. Chem., 56, 987-997.
39. Faustino, N.A. and Cooper, T.A. (2003) Pre-mRNA splicing and human disease. Genes Dev., 17, 419-437.
40. Venables, J.P. (2004) Aberrant and alternative splicing in cancer. Cancer Res., 64, 7647-7654.
41. Trapnell, C., Williams, B.A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M.J., Salzberg, S.L., Wold, B.J. and Pachter, L. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol., 28, 511-515.
42. Guttman, M., Garber, M., Levin, J.Z., Donaghey, J., Robinson, J., Adiconis, X., Fan, L., Koziol, M.J., Gnirke, A., Nusbaum, C. et al. (2010) Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat. Biotechnol., 28, 503-510.
43. Aschoff, M., Hotz-Wagenblatt, A., Glatting, K.H., Fischer, M., Eils, R. and König, R. (2013) SplicingCompass: differential splicing detection using RNA-seq data. Bioinformatics, 29, 1141-1148.