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seqgendiff (version 1.2.4)

ThinDataToDESeqDataSet: Converts a ThinData S3 object into a DESeqDataSet S4 object.

Description

The design formula in the resulting DESeqDataSet is just the sum of all variables in designmat from the ThinData object (except the intercept term). You should change this design formula if you want to study other models.

Usage

ThinDataToDESeqDataSet(obj)

Value

A DESeqDataSet S4 object. This will allow you to insert the simulated data directly into DESeq2.

Arguments

obj

A ThinData S3 object. This is generally output by either thin_diff, thin_2group, thin_lib, thin_gene, or thin_all.

Author

David Gerard

Examples

Run this code
# \donttest{
## 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 DESeqDataSet object.
seobj <- ThinDataToDESeqDataSet(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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