ecScore {myTAI}

Compute the Hourglass Score for the EarlyConservationTest

Description

This function computes the EarlyConservationTest score for a given TAI or TDI pattern.

The reductive early conservation test is a permutation test based on the following test statistic.

- A set of developmental stages is partitioned into three modules - early, mid, and late - based on prior biological knowledge.

- The mean TAI or TDI value for each of the three modules T_early, T_mid, and T_late are computed.

- The two differences D1 = T_mid - T_early and D2 = T_late - T_early are calculated.

- The minimum D_min of D1 and D2 is computed as final test statistic of the reductive hourglass test.

This function ecScore computes the D_min value for a given TAI or TDI stored in the age_vals argument.

Usage

ecScore(age_vals, early, mid, late)

Arguments

age_vals

a numeric vector containing TAI or TDI values for each developmental stage s.

early

a numeric vector storing the numeric stage values that correspond to the early phase of development.

mid

a numeric vector storing the numeric stage values that correspond to the middle phase of development.

late

a numeric vector storing the numeric stage values that correspond to the late phase of development.

Value

a numeric value representing the early conservation score.

Author(s)

Hajk-Georg Drost

See Also

EarlyConservationTest, TAI, TDI

Examples

 # read standard phylotranscriptomics data
 data(PhyloExpressionSetExample)
 data(DivergenceExpressionSetExample)

 # Example PhyloExpressionSet:

 # compute the TAI profile
 TAIs <- TAI(PhyloExpressionSetExample)

 # compute the early conservation score for the TAI profile
 ec_score <- ecScore(age_vals = TAIs,early = 1:2,mid = 3:5,late = 6:7)


 # Example DivergenceExpressionSet:

 # compute the TDI profile
 TDIs <- TDI(DivergenceExpressionSetExample)

 # compute the early conservation score for the TDI profile
 ec_score <- ecScore(age_vals = TDIs,early = 1:2,mid = 3:5,late = 6:7)
 
 # compute ecScore() vector from bootMatrix()
 apply(bootMatrix(PhyloExpressionSetExample,10),1,ecScore,early = 1:2,mid = 3:5,late = 6:7)