EMPOWERING MULTI-COHORT GENE EXPRESSION ANALYSIS TO INCREASE REPRODUCIBILITY.
Pac Symp Biocomput
; 22: 144-153, 2017.
Article
em En
| MEDLINE
| ID: mdl-27896970
ABSTRACT
A major contributor to the scientific reproducibility crisis has been that the results from homogeneous, single-center studies do not generalize to heterogeneous, real world populations. Multi-cohort gene expression analysis has helped to increase reproducibility by aggregating data from diverse populations into a single analysis. To make the multi-cohort analysis process more feasible, we have assembled an analysis pipeline which implements rigorously studied meta-analysis best practices. We have compiled and made publicly available the results of our own multi-cohort gene expression analysis of 103 diseases, spanning 615 studies and 36,915 samples, through a novel and interactive web application. As a result, we have made both the process of and the results from multi-cohort gene expression analysis more approachable for non-technical users.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Perfilação da Expressão Gênica
Tipo de estudo:
Etiology_studies
/
Guideline
/
Incidence_studies
/
Observational_studies
/
Risk_factors_studies
/
Systematic_reviews
Limite:
Humans
Idioma:
En
Revista:
Pac Symp Biocomput
Assunto da revista:
BIOTECNOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos