ThinDataToSummarizedExperiment  R Documentation 
This only keeps the mat
, design_obs
, designmat
,
and coefmat
elements of the ThinData object.
ThinDataToSummarizedExperiment(obj)
obj 
A ThinData S3 object. This is generally output by either

A SummarizedExperiment
S4
object. This is often used in Bioconductor when performing
differential expression analysis.
David Gerard
## Generate simulated data and modify using thin_diff(). ## In practice, you would use real data, not simulated. set.seed(1) n < 10 p < 1000 Z < matrix(abs(rnorm(n, sd = 4))) alpha < matrix(abs(rnorm(p, sd = 1))) mat < round(2^(alpha %*% t(Z) + abs(matrix(rnorm(n * p, sd = 5), nrow = p, ncol = n)))) design_perm < cbind(rep(c(0, 1), length.out = n), runif(n)) coef_perm < matrix(rnorm(p * ncol(design_perm), sd = 6), nrow = p) design_obs < matrix(rnorm(n), ncol = 1) target_cor < matrix(c(0.9, 0)) thout < thin_diff(mat = mat, design_perm = design_perm, coef_perm = coef_perm, target_cor = target_cor, design_obs = design_obs, permute_method = "hungarian") ## Convert ThinData object to SummarizedExperiment object. seobj < ThinDataToSummarizedExperiment(thout) class(seobj) ## The "O1" variable in the colData corresponds to design_obs. ## The "P1" and "P2" variables in colData correspond to design_perm. seobj
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