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Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types.

ABSTRACT: BACKGROUND: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in standard meta-analysis approaches (such as the inverse variance method) to obtain large sample sizes for statistical power enrichment. Noting that plenty of normal tissue microarray samples exist in studies not involving cancer, we investigated the viability and accuracy of an integrated microarray analysis approach based on significance analysis of microarrays (merged SAM) using a collection of data from separate diseased and normal samples. RESULTS: We focused on five solid cancer types (colon, kidney, liver, lung, and pancreas), where available microarray data allowed us to compare meta-analysis and integrated approaches. Our results from the merged SAM significantly overlapped gene lists from the validated inverse-variance method. Both meta-analysis and merged SAM approaches successfully captured the aberrances in the cell cycle that commonly occur in the different cancer types. However, the integrated SAM analysis replicated the known cancer literature (excluding microarray studies) with much more accuracy than the meta-analysis. CONCLUSION: The merged SAM test is a powerful, robust approach for combining data from similar platforms and for analyzing asymmetric datasets, including those with only normal or only cancer samples that cannot be utilized by meta-analysis methods. The integrated SAM approach can also be used in comparing global gene expression between various subtypes of cancer arising from the same tissue.

SUBMITTER: Dawany NB

PROVIDER: S-EPMC2949900 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types.

Dawany Noor B NB Tozeren Aydin A

BMC bioinformatics 20100927

<h4>Background</h4>Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in standard meta-analysis approaches (such as the inverse variance method) to obtain large sample sizes for statistical power enrichment. Noting that plenty of normal tissue microarray samples exist in studies not involving cancer, we investigated the viability and accuracy of an integrated microarray analysis approach b ...[more]

PMID: 20875095

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Project description:Background & aimsThe colon is innervated by intrinsic and extrinsic neurons that coordinate functions necessary for digestive health. Sympathetic input suppresses colon motility by acting on intrinsic myenteric neurons, but the extent of sympathetic-induced changes on large-scale network activity in myenteric circuits has not been determined. Compounding the complexity of sympathetic function, there is evidence that sympathetic transmitters can regulate activity in non-neuronal cells (such as enteric glia and innate immune cells).MethodsWe performed anatomical tracing, immunohistochemistry, optogenetic (GCaMP calcium imaging, channelrhodopsin), and colon motility studies in mice and single-cell RNA sequencing in human colon to investigate how sympathetic postganglionic neurons modulate colon function.ResultsIndividual neurons in each sympathetic prevertebral ganglion innervated the proximal or distal colon, with processes closely opposed to multiple cell types. Calcium imaging in semi-intact mouse colon preparations revealed changes in spontaneous and evoked neural activity, as well as activation of non-neuronal cells, induced by sympathetic nerve stimulation. The overall pattern of response to sympathetic stimulation was unique to the proximal or distal colon. Region-specific changes in cellular activity correlated with motility patterns produced by electrical and optogenetic stimulation of sympathetic pathways. Pharmacology experiments (mouse) and RNA sequencing (human) indicated that appropriate receptors were expressed on different cell types to account for the responses to sympathetic stimulation. Regional differences in expression of α-1 adrenoceptors in human colon emphasize the translational relevance of our mouse findings.ConclusionsSympathetic neurons differentially regulate activity of neurons and non-neuronal cells in proximal and distal colon to promote distinct changes in motility patterns, likely reflecting the distinct roles played by these 2 regions.

Project description:Answering questions such as "Which genes are related to breast cancer?" usually requires retrieving relevant publications through the PubMed search engine, reading these publications, and creating gene lists. This process is not only time-consuming, but also prone to errors.We report GLAD4U (Gene List Automatically Derived For You), a new, free web-based gene retrieval and prioritization tool. GLAD4U takes advantage of existing resources of the NCBI to ensure computational efficiency. The quality of gene lists created by GLAD4U for three Gene Ontology (GO) terms and three disease terms was assessed using corresponding "gold standard" lists curated in public databases. For all queries, GLAD4U gene lists showed very high recall but low precision, leading to low F-measure. As a comparison, EBIMed's recall was consistently lower than GLAD4U, but its precision was higher. To present the most relevant genes at the top of a list, we studied two prioritization methods based on publication count and the hypergeometric test, and compared the ranked lists and those generated by EBIMed to the gold standards. Both GLAD4U methods outperformed EBIMed for all queries based on a variety of quality metrics. Moreover, the hypergeometric method allowed for a better performance by thresholding genes with low scores. In addition, manual examination suggests that many false-positives could be explained by the incompleteness of the gold standards. The GLAD4U user interface accepts any valid queries for PubMed, and its output page displays the ranked gene list and information associated with each gene, chronologically-ordered supporting publications, along with a summary of the run and links for file export and functional enrichment and protein interaction network analysis.GLAD4U has a high overall recall. Although precision is generally low, the prioritization methods successfully rank truly relevant genes at the top of the lists to facilitate efficient browsing. GLAD4U is simple to use, and its interface can be found at: http://bioinfo.vanderbilt.edu/glad4u.

Dataset Information

Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types.

Publications

Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types.

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