학술논문
Targeted exploration and analysis of large cross-platform human transcriptomic compendia
Document Type
Report
Author
Source
Nature Methods. March 1, 2015, p211, 7 p.
Subject
Language
English
ISSN
1548-7091
Abstract
The accumulation of human gene expression data in public repositories, such as The Cancer Genome Atlas (1) and Gene Expression Omnibus (2), offers unprecedented opportunities for data-driven characterization of biological [...]
We present sEEK (search-based exploration of expression compendia; http://seek.princeton.edu/), a query-based search engine for very large transcriptomic data collections, including thousands of human data sets from many different microarray and high-throughput sequencing platforms. sEEK uses a query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify genes, pathways and processes co-regulated with the query. SEEK provides multigene query searching with iterative metadata-based search refinement and extensive visualization-based analysis options.
We present sEEK (search-based exploration of expression compendia; http://seek.princeton.edu/), a query-based search engine for very large transcriptomic data collections, including thousands of human data sets from many different microarray and high-throughput sequencing platforms. sEEK uses a query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify genes, pathways and processes co-regulated with the query. SEEK provides multigene query searching with iterative metadata-based search refinement and extensive visualization-based analysis options.