gls.series_multiple_designs: limma gls.series adapted for varying covariates across genes
In jhsiao999/Humanzee: Tools for statistical analysis of genomics data

Description Usage Arguments Examples

This function tests for divergence between two species in one molecular phenotype at a time. The current version is tuned for Brett's diffphos analysis.

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gls.series_multiple_designs(M, cov_matrix = NULL, design = NULL,
  ndups = 1, spacing = 1, block = NULL, correlation = NULL,
  weights = NULL, ...)

`M`	Matrix of gene by sample.
`cov_matrix`	Matrix of gene specific covariate information (gene by sample).
`design`	Model matrix, the part that is fixed across genes, indepenent of cov_matrix.

M <- phos_data
cov_matrix <- protein_pheno_data
individual <- as.numeric(str_extract(colnames(phos_data), "[0-9]+"))
design <- model.matrix(~ 1 + as.factor(individual))
block <- block
correlation <- mrho
ndups = 1; weights = NULL; spacing = 1