Integrative analysis of independent transcriptome data for rare diseases.

ABSTRACT: High-throughput technologies used to interrogate transcriptomes have been generating a great amount of publicly available gene expression data. For rare diseases that lack of clinical samples and research funding, there is a practical benefit to jointly analyze existing data sets commonly related to a specific rare disease. In this study, we collected a number of independently generated transcriptome data sets from four species: human, fly, mouse and worm. All data sets included samples with both normal and abnormal mitochondrial function. We reprocessed each data set to standardize format, scale and gene annotation and used HomoloGene database to map genes between species. Standardized procedure was also applied to compare gene expression profiles of normal and abnormal mitochondrial func

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC5014495 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature