Difference between revisions of "Meta analysis"
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| + | ;Analysis title | ||
| + | :[[File:Statistics-Meta-analysis-icon.png]] Meta analysis | ||
| + | ;Provider | ||
| + | :[[Institute of Systems Biology]] | ||
| + | ;Class | ||
| + | :{{Class|ru.biosoft.analysis.MetaAnalysis}} | ||
| + | ;Plugin | ||
| + | :[[Ru.biosoft.analysis (plugin)|ru.biosoft.analysis (Common methods of data analysis plug-in)]] | ||
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=== Meta-analysis === | === Meta-analysis === | ||
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[[Category:Analyses]] | [[Category:Analyses]] | ||
[[Category:Statistics (analyses group)]] | [[Category:Statistics (analyses group)]] | ||
| + | [[Category:ISB analyses]] | ||
| + | [[Category:Autogenerated pages]] | ||
Latest revision as of 11:15, 31 May 2013
- Analysis title
Meta analysis
- Provider
- Institute of Systems Biology
- Class
MetaAnalysis- Plugin
- ru.biosoft.analysis (Common methods of data analysis plug-in)
[edit] Meta-analysis
The aim of a meta-analysis is to identify up- and down-regulated genes from different independent microarray experiments. Such a meta-analysis is based on the hypergeometric analysis method. Within the framework of a meta-analysis, a hypergeometric analysis is applied to sets of gene profiles. The obtained results are the initial data for a subsequent meta-analysis. It uses the same procedure as a hypergeometric analysis for testing the hypothesis that the that score obtained in previous tests deviates from 0 (Boundary Value = 0) just by chance. The result is a table with meta scores that indicate.
[edit] Parameters:
- Tables - tables from the input data collection to be used for the meta analysis
- Note: for proper work tables should have only one column with scores obtained by Hypergeometric analysis (without fold change, details or annotations).
- Output type - the type of genes to be included in result:
- Up- and down-regulated
- Up-regulated
- Down-regulated
- P-value threshold - threshold for P-value (only elements with lower P-value will be included in the results).
- Calculate FDR - the test method for calculation of False Discovery Rate (FDR) - an average rate of mistakenly found up- or down-regulated genes under the given P-value threshold. It randomly permutates the data 50 times and applies the selected meta-analysis to each randomized table. FDR is calculated separately for up- and down-regulated genes according to the formula:
- Output table - the path in the BioUML repository where the result table will be stored. If a table with the specified path already exists it will be replaced.
