Comparison of approaches to transcriptomic analysis in multi-sampled tumors.
Brief Bioinform
; 22(6)2021 11 05.
Article
em En
| MEDLINE
| ID: mdl-34415294
ABSTRACT
Intratumoral heterogeneity is a well-documented feature of human cancers and is associated with outcome and treatment resistance. However, a heterogeneous tumor transcriptome contributes an unknown level of variability to analyses of differentially expressed genes (DEGs) that may contribute to phenotypes of interest, including treatment response. Although current clinical practice and the vast majority of research studies use a single sample from each patient, decreasing costs of sequencing technologies and computing power have made repeated-measures analyses increasingly economical. Repeatedly sampling the same tumor increases the statistical power of DEG analysis, which is indispensable toward downstream analysis and also increases one's understanding of within-tumor variance, which may affect conclusions. Here, we compared five different methods for analyzing gene expression profiles derived from repeated sampling of human prostate tumors in two separate cohorts of patients. We also benchmarked the sensitivity of generalized linear models to linear mixed models for identifying DEGs contributing to relevant prostate cancer pathways based on a ground-truth model.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Perfilação da Expressão Gênica
/
Transcriptoma
/
Neoplasias
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
/
Male
Idioma:
En
Revista:
Brief Bioinform
Assunto da revista:
BIOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos