Indirect genomic effects on survival from gene expression data.
In cancer, genes may have indirect effects on patient survival, mediated through interactions with other genes. Methods to study the indirect effects that contribute significantly to survival are not available. We propose a novel methodology to detect and quantify indirect effects from gene expression data. We discover indirect effects through several target genes of transcription factors in cancer microarray data, pointing to genetic interactions that play a significant role in tumor progression.
Ferkingstad
Egil
E
Department of Biostatistics and (sfi) Statistics for Innovation, University of Oslo, Gaustadalleen, Oslo, NO-0314, Norway. egil.ferkingstad@medisin.uio.no
Frigessi
Arnoldo
A
Lyng
Heidi
H
D019295:Computational Biology / Q000379:methods*; D005260:Female; D015870:Gene Expression; D023281:Genomics; D006801:Humans; D008297:Male; D009369:Neoplasms / Q000235:genetics* / Q000401:mortality*; D020411:Oligonucleotide Array Sequence Analysis; D012044:Regression Analysis; D014157:Transcription Factors / Q000235:genetics*
D014157:Transcription Factors