EMPOWERING MULTI-COHORT GENE EXPRESSION ANALYSIS TO INCREASE REPRODUCIBILITY.
Pac Symp Biocomput
; 22: 144-153, 2017.
Article
en 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
Base de datos:
MEDLINE
Asunto principal:
Perfilación de la Expresión Génica
Tipo de estudio:
Etiology_studies
/
Guideline
/
Incidence_studies
/
Observational_studies
/
Risk_factors_studies
/
Systematic_reviews
Idioma:
En
Revista:
Pac Symp Biocomput
Asunto de la revista:
BIOTECNOLOGIA
/
INFORMATICA MEDICA
Año:
2017
Tipo del documento:
Article