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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 early conservation 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, profile.warn = FALSE)

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.

profile.warn

a boolean value indicating whether a warning is printed when a low-mid-high pattern isn't followed.

Value

a numeric value representing the early conservation score.

Author

Hajk-Georg Drost

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)
#> 
#> [ Number of Eigen threads that are employed on your machine: 12 ]
#> 
#> [ Computing age assignment permutations for test statistic ... ]
#> 
[=========================================] 100%   
#> [ Computing variances of permuted transcriptome signatures ... ]
#> 
#>           1           2           3           4           5           6 
#> -0.05681366 -0.02292928 -0.05911419 -0.04578738 -0.02225435 -0.02986441 
#>           7           8           9          10 
#>  0.01308162 -0.03649770  0.04031555 -0.04323258 
 
 # get warning if the expected pattern isn't followed
 ec_score <- ecScore(age_vals = TAIs,early = 1:2,mid = 3:5,late = 6:7,profile.warn=TRUE)
#> The phylotranscriptomic pattern may not follow an early conservation pattern (low-mid-high or low-high-high).