Comparative analysis of algorithms for integration of copy number and expression data

ABSTRACT: Chromosomal instability is a hallmark of cancer and genes that display abnormal expression in chromosomally aberrant regions are likely to be key players in tumor progression. Identifying such driver genes from high-throughput data requires computational methods that are capable of integrating data from several sources and thereby enhance the reliability of driver gene identification. Hence, several algorithms that integrate copy number and expression data have been developed but their relative performance has not been assessed so far. We have compared 10 algorithms that integrate high-throughput copy number and transcriptomics data using simulated, cancer cell line and primary tumor data. Our results show that there are significant differences between the methods and their performance decreases significantly with small sample sets. Head and neck squamous cell carcinoma (HNSCC) cell lines from the tongue (UT-SCC-21,UT-SCC-24B, UT-SCC-30, UT-SCC-67, UT-SCC-73, UT-SCC-76A, UT-SCC-81, UT-SCC-87,UT-SCC-95) and larynx (UT-SCC-8, UT-SCC-11, UT-SCC-75) were provided by the Department of Otorhinolaryngology-Head and Neck Surgery at the Turku University Central Hospital (Turku, Finland). HNSCC cell lines SCC-4, SCC-9, SCC-25 and human skin keratinocyte HPV-16 E6/E7 transformed cell line CCD1106 KERTr was ordered from American Type Culture Collection (ATCC; Manassas, VA) and cultured according to the ATCC recommendations.

ORGANISM(S): Homo sapiens

DISEASE(S): normal

SUBMITTER: Riku Louhimo 

PROVIDER: E-MEXP-3415 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress