inst/extdata/crouzon/README.md

In psolymos/EDMAinR: Euclidean Distance Matrix Analysis in R

The attached data were used in the publication that is attached to this email (dvdy.23903.pdf). Files contain landmarks collected from CT images of P0 (newborn) mice. There are two sets of data. Each set contains data from one sample of mice that carry a mutation when present in humans causes a disease called Crouzon syndrome and a sample of their unaffected litter-mates.

Set #1 -File 1: "Crouzon_P0_Global_NON-MUT.xyz" (data file containing data for mice NOT carrying the mutation used as the numerator file in analysis) K=47 N=31 -File 2: "Crouzon_P0_Global_MUT.xyz" (data file containing landmarks for mice carrying the mutation used as the denominator file in analysis) K=47 N=28 -File 3: "Crouzon global out.txt" output from EDMA analysis

Sample sizes and landmark labels are included in the data files. In these files K>N but for hypothesis testing we used subsets of landmarks. The confidence intervals should provide information. I can send you any output from subsets or subset files if you want to check that but I thought files with bigger numbers of landmarks might be good? This makes me remember that the current EDMA software limits sample sizes to 50 - which should be expanded for the R version.

Set #2 -File 1: "Crouzon_P0_face_Non-Mut2.xyz" (data file containing data for mice NOT carrying the mutation used as the numerator file in analysis) K=22 N=31 -File 2: "Crouzon_P0_face_Mut2.xyz" (data file containing landmarks for mice carrying the mutation used as the denominator file in analysis) K=22 N=28 -File 3: "Crouzon _P0_face_ETHMA_OUTPUT.txt" output from EDMA analysis

These files contain a subset of landmarks (from the facial skeleton) from the samples above.

psolymos/EDMAinR documentation built on Aug. 25, 2023, 7:54 p.m.