SAMHelper (FSharp.Stats)

SAMHelper Module

Namespace: FSharp.Stats.Testing
Assembly: FSharp.Stats.dll
Parent Module: SAM

Functions and values

Function or value	Description
`estimatePi0 obsStats expStats` Full Usage: `estimatePi0 obsStats expStats` Parameters: obsStats : `SAM<'a>[]` expStats : `SAM<'b>[][]` Returns: `float`	estimate pi0 using the quantile method. Helps to not overestimate the False Discovery Rate obsStats : `SAM<'a>[]` expStats : `SAM<'b>[][]` Returns: `float`
`fdrsPerCut cuts expStats obsStats pi0` Full Usage: `fdrsPerCut cuts expStats obsStats pi0` Parameters: cuts : `((float * float) * 'a) array` expStats : `SAM<'b>[] array` obsStats : `SAM<'c>[]` pi0 : `float` Returns: `((float * float) * float) array`	Calculate the FDR for each cut cuts : `((float * float) * 'a) array` expStats : `SAM<'b>[] array` obsStats : `SAM<'c>[]` pi0 : `float` Returns: `((float * float) * float) array`
`getDeltaAndAsymmCuts obsStats expAvgStats` Full Usage: `getDeltaAndAsymmCuts obsStats expAvgStats` Parameters: obsStats : `SAM<'a>[]` expAvgStats : `SAM<'b>[]` Returns: `((float * float) * float) array`	default in R!. Calculates asymmetric cuts for each delta present. obsStats : `SAM<'a>[]` expAvgStats : `SAM<'b>[]` Returns: `((float * float) * float) array`
`getMedianFalsePositives (arg1, arg2) expStats` Full Usage: `getMedianFalsePositives (arg1, arg2) expStats` Parameters: arg0 : `float` arg1 : `float` expStats : `SAM<'a>[] array` Returns: `float`	median false positives are obtained by counting how many statistics (from permuted data) fall outside of the cuts by chance. Permuted data should show no effect/change, therefor the ones that do are false positive arg0 : `float` arg1 : `float` expStats : `SAM<'a>[] array` Returns: `float`
`getMedianFdr pi0 medianFalsePos significantBioitems` Full Usage: `getMedianFdr pi0 medianFalsePos significantBioitems` Parameters: pi0 : `float` medianFalsePos : `float` significantBioitems : `float` Returns: `float`	calculate the median False Discovery Rate pi0 : `float` medianFalsePos : `float` significantBioitems : `float` Returns: `float`
`getQvalues obsStats negativeCut positiveCut` Full Usage: `getQvalues obsStats negativeCut positiveCut` Parameters: obsStats : `SAM<'a> array` negativeCut : `(float * float) array` positiveCut : `(float * float) array` Returns: `SAM<'a> array`	returns the value for each sample where it is firstly called significantly different. obsStats : `SAM<'a> array` negativeCut : `(float * float) array` positiveCut : `(float * float) array` Returns: `SAM<'a> array`
`getSignificantBioitem (arg1, arg2) obsStats` Full Usage: `getSignificantBioitem (arg1, arg2) obsStats` Parameters: arg0 : `float` arg1 : `float` obsStats : `SAM<'a>[]` Returns: `int`	amount of Bioitems that are more extreme than the cuts and therefor are called significant arg0 : `float` arg1 : `float` obsStats : `SAM<'a>[]` Returns: `int`
`monotonizeDecreasing accessionFun replaceFun input` Full Usage: `monotonizeDecreasing accessionFun replaceFun input` Parameters: accessionFun : `'a -> float` replaceFun : `'a -> float -> 'a` input : `'a[]` Returns: `'a array`	ensures continuous decrease of data. accessionFun : `'a -> float` replaceFun : `'a -> float -> 'a` input : `'a[]` Returns: `'a array`
`monotonizeIncreasing accessionFun replaceFun input` Full Usage: `monotonizeIncreasing accessionFun replaceFun input` Parameters: accessionFun : `'a -> float` replaceFun : `'a -> float -> 'a` input : `'a[]` Returns: `'a array`	ensures continuous increase of data. accessionFun : `'a -> float` replaceFun : `'a -> float -> 'a` input : `'a[]` Returns: `'a array`
`negCutToFDR fdrsPerCut` Full Usage: `negCutToFDR fdrsPerCut` Parameters: fdrsPerCut : `(('a * 'b) * float) array` Returns: `('a * float) array`	obtain negative cut for chosen FDR fdrsPerCut : `(('a * 'b) * float) array` Returns: `('a * float) array`
`posCutToFDR fdrsPerCut` Full Usage: `posCutToFDR fdrsPerCut` Parameters: fdrsPerCut : `(('a * 'b) * float) array` Returns: `('b * float) array`	obtain positive cut for chosen FDR fdrsPerCut : `(('a * 'b) * float) array` Returns: `('b * float) array`
`smallestCutAndDeltaForFDR cuts expStats obsStats fdr pi0` Full Usage: `smallestCutAndDeltaForFDR cuts expStats obsStats fdr pi0` Parameters: cuts : `((float * float) * 'a) array` expStats : `SAM<'b>[] array` obsStats : `SAM<'c>[]` fdr : `float` pi0 : `float` Returns: `(float * float) * 'a`	get the smallest cut and corresponding delta for chosen FDR cuts : `((float * float) * 'a) array` expStats : `SAM<'b>[] array` obsStats : `SAM<'c>[]` fdr : `float` pi0 : `float` Returns: `(float * float) * 'a`