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

In seqgendiff: RNA-Seq Generation/Modification for Simulation

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)

Arguments

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

Value

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

Author(s)

David Gerard

Examples

## 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

seqgendiff documentation built on March 18, 2022, 5:21 p.m.