Dataset Information

Targeted exploration and analysis of large cross-platform human transcriptomic compendia.

ABSTRACT: 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.

SUBMITTER: Zhu Q

PROVIDER: S-EPMC4768301 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Targeted exploration and analysis of large cross-platform human transcriptomic compendia.

Zhu Qian Q Wong Aaron K AK Krishnan Arjun A Aure Miriam R MR Tadych Alicja A Zhang Ran R Corney David C DC Greene Casey S CS Bongo Lars A LA Kristensen Vessela N VN Charikar Moses M Li Kai K Troyanskaya Olga G OG

Nature methods 20150112 3

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. ...[more]

PMID: 25581801

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Project description:BackgroundMicroarrays are the main technology for large-scale transcriptional gene expression profiling, but the large bodies of data available in public databases are not useful due to the large heterogeneity. There are several initiatives that attempt to bundle these data into expression compendia, but such resources for bacterial organisms are scarce and limited to integration of experiments from the same platform or to indirect integration of per experiment analysis results.Methodology/principal findingsWe have constructed comprehensive organism-specific cross-platform expression compendia for three bacterial model organisms (Escherichia coli, Bacillus subtilis, and Salmonella enterica serovar Typhimurium) together with an access portal, dubbed COLOMBOS, that not only provides easy access to the compendia, but also includes a suite of tools for exploring, analyzing, and visualizing the data within these compendia. It is freely available at http://bioi.biw.kuleuven.be/colombos. The compendia are unique in directly combining expression information from different microarray platforms and experiments, and we illustrate the potential benefits of this direct integration with a case study: extending the known regulon of the Fur transcription factor of E. coli. The compendia also incorporate extensive annotations for both genes and experimental conditions; these heterogeneous data are functionally integrated in the COLOMBOS analysis tools to interactively browse and query the compendia not only for specific genes or experiments, but also metabolic pathways, transcriptional regulation mechanisms, experimental conditions, biological processes, etc.Conclusions/significanceWe have created cross-platform expression compendia for several bacterial organisms and developed a complementary access port COLOMBOS, that also serves as a convenient expression analysis tool to extract useful biological information. This work is relevant to a large community of microbiologists by facilitating the use of publicly available microarray experiments to support their research.

Dataset Information

Targeted exploration and analysis of large cross-platform human transcriptomic compendia.

Publications

Targeted exploration and analysis of large cross-platform human transcriptomic compendia.

Similar Datasets

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