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perseus:user:activities:matrixprocessing:outliers:significancea
Table of Contents
Significance A
General
- Type: Matrix Processing
- Heading: Outliers
Brief description
Determines which values are significant outliers relative to a certain population. For details see Cox and Mann (2008) Nat. Biotech. 26, 1367-72.
Output: A numerical column is added containing the significance A value. Furthermore, a categorical column is added indicating by '+' if a row is significant.
Parameters
Columns
Selected expression columns for which “Significance A” should be calculated (default: no expression columns are selected).
Side
To apply a two-sided test, where the null hypothesis can be rejected regardless of the direction of the effect “both” has to be selected (default). “left” and “right” are the respective one-sided tests.
Use for truncation
The truncation can be based on p-values or the Benjamini-Hochberg correction for multiple hypothesis testing (default: Benjamini-Hochberg FDRFalse Discovery Rate). Rows with a test result below a specified value (parameter below) are reported as significant.
Threshold value
Based on a specified threshold a specific row is reported as significant (default: 0.05). Depending on the chosen truncation score this threshold value is applied to the p-value or to the Benjamini-Hochberg FDR.
Parameter window
perseus/user/activities/matrixprocessing/outliers/significancea.txt · Last modified: 2015/11/23 14:47 (external edit)
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