An online database for brain disease research - PubMed (original) (raw)

An online database for brain disease research

Brandon W Higgs et al. BMC Genomics. 2006.

Abstract

Background: The Stanley Medical Research Institute online genomics database (SMRIDB) is a comprehensive web-based system for understanding the genetic effects of human brain disease (i.e. bipolar, schizophrenia, and depression). This database contains fully annotated clinical metadata and gene expression patterns generated within 12 controlled studies across 6 different microarray platforms.

Description: A thorough collection of gene expression summaries are provided, inclusive of patient demographics, disease subclasses, regulated biological pathways, and functional classifications.

Conclusion: The combination of database content, structure, and query speed offers researchers an efficient tool for data mining of brain disease complete with information such as: cross-platform comparisons, biomarkers elucidation for target discovery, and lifestyle/demographic associations to brain diseases.

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Figures

Figure 1

Figure 1

QC histograms. Examples of distribution thresholds used to assess outliers for an individual study.

Figure 2

Figure 2

Demographic gene table. Table of genes determined to be significant (p < 0.01 and fold change > 1.3) with the demographic variables for an individual study.

Figure 3

Figure 3

Disease gene table. Table of genes determined to be significant (p < 0.01 and fold change > 1.3) with the disease for an individual study.

Figure 4

Figure 4

Study-level visuals (heatmap). Two-dimensional hierarchical clustering heatmap containing the most significant genes in schizophrenic disease for an individual study.

Figure 5

Figure 5

Study-level visuals (PCA scatter plot). Principal components plots generated with the most significant genes in schizophrenic disease for an individual study.

Figure 6

Figure 6

Pathway table. Table of most regulated pathways for an individual study.

Figure 7

Figure 7

Fold change boxplots. Fold change (with confidence intervals) values for bipolar patients for every gene that maps to the Alzheimer's pathway.

Figure 8

Figure 8

Gene summary page (truncated). Portion of gene summary page for the gene reelin (RELN).

Figure 9

Figure 9

Fold change boxplots. Fold change (with 99% confidence intervals) for the gene reelin across all 41 demographic variables.

Figure 10

Figure 10

Summary statistic table. Gene-level summary table of significant probes across all studies for depression.

Figure 11

Figure 11

Pathway clickable heatmap. Study-centric clickable heatmap of top regulated pathways in schizophrenia. Each column can be sorted by a particular study or the three last summary columns. Study 12 was omitted from this visual.

Figure 12

Figure 12

GO term clickable heatmap. Gene-centric clickable heatmap of top regulated GO terms (molecular function) in schizophrenia. Each column can be sorted by a disease.

Figure 13

Figure 13

Pathway/demographic clickable heatmap. Demographic variable clickable heatmap of top regulated pathways. Each column can be sorted by a demographic variable.

References

    1. Pavlidis P, Noble WS. Analysis of strain and regional variation in gene expression in mouse brain. Genome Biology. 2001;2:RESEARCH0042. doi: 10.1186/gb-2001-2-10-research0042. - DOI - PMC - PubMed
    1. Cho H, Lee JK. Bayesian hierarchical error model for analysis of gene expression data. Bioinformatics. 2001;20:2016–25. doi: 10.1093/bioinformatics/bth192. - DOI - PubMed
    1. Iacobas DA, Urban M, Iacobas S, Spray DC. Control and variability of gene expression in mouse brain and in a neuroblastoma cell line. Rom J Physiol. 2003;39–40:2002–71. - PubMed
    1. Jurata LW, Bukhman YV, Charles V, Capriglione F, Bullard J, Lemire AL, Mohammed A, Pham Q, Laeng P, Brockman JA, Altar CA. Comparison of microarray-based mRMA profiling technologies for identification of psychiatric disease and drug signatures. J Neurosci Methods. 2004;138:173–88. doi: 10.1016/j.jneumeth.2004.04.002. - DOI - PubMed
    1. Kuo WP, Jenssen TK, Butte AJ, Ohno-Machado L, Kohane IS. Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics. 2002;18:405–412. doi: 10.1093/bioinformatics/18.3.405. - DOI - PubMed

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