F1.SCORE.FOR.SPARSE: F1.SCORE.FOR.SPARSE : F1 score for sparse LFMM package (for...

In jumentib/useFonc: Useful Functions

Description

F1.SCORE.FOR.SPARSE : F1 score for sparse LFMM package (for simulation)

Usage

F1.SCORE.FOR.SPARSE(a, b, causal)

Arguments

a	alpha effect in mediation (sparse_lfmm$B[,1])
b	beta effect in mediation (sparse_lfmm$B[,2])
causal	true result of the simulation

Details

Select the markers with a * b != 0 F1 = 2*recall*power/(recall + power)

Value

precision : statistical precision of the test : TP / (TP + FP)

recall : statistical recall of the test : TP / (TP + FN)

f1_score : F1 Score of the test : 2(Pre * Rec) / (Pre + Rec)

length.list : number of pValues lower than "ral" (Bonferroni correction).

TP : True positive

FP : False positive

FN : False negative

jumentib/useFonc documentation built on Nov. 18, 2019, 3:17 p.m.