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We also observed divergence in the P- and G-matrices for populations that experienced different environmental conditions.
Haplotypes were collapsed using FaBox [ 112] and translated into a genotype matrix for population genetics analyses.
Top six principal components were used to build up the P matrix for population structure correction in the two panels.
The top six principal components were used to build up the P matrix for population structure correction in the two panels.
To calculate correlations between SNP allele frequencies and current and past climate variables, we used the Bayesian linear model method of Coop et al. (2010), which controls for population history by incorporating a covariance matrix of populations and accounts for differences in sample size between populations.
To explore such a correlation in a quantitative way, we statistically compared genetic, geographic and linguistic distance matrices for our population datasets (see Table S5 for detailed matrix data).
Within- and between-population covariance matrices for T. moorii populations deviated from proportionality.
Additional file 2 (AF2) shows the LD matrix for all populations and for each breed separately and also a figure of LD blocks and haplotypes.
JMP Genomics 7.1 (SAS Institute, Cary, NC) was used to perform the genome-wide association analysis and to generate covariate matrices to account for population structure (Q-matrix) and genetic relatedness (K-matrix).
Additional evidence of selective processes comes from the comparison between within-population and between-population covariance matrices for the studied T. moorii populations.
Our approach involved first constructing a population-specific consolidated map by merging constituent genotype matrices for each mapping population following initial assignment to each of the 19 LGs.
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