chooseSigma: Select the threshold sigma for hd-MI.

In RNAseqNet: Log-Linear Poisson Graphical Model with Hot-Deck Multiple Imputation

Description

chooseSigma computes the average intra-donor pool variance for different values of sigma. It helps choosing a sigma that makes a good trade-off between homogeneity within the pool of donors and variety (large enough number of donors in every pool).

Usage

chooseSigma(X, Y, sigma_list, seed = NULL)

Arguments

X	n x p numeric matrix containing RNA-seq expression with missing rows (numeric matrix or data frame)
Y	auxiliary dataset (n' x q numeric matrix or data frame)
sigma_list	a sequence of increasing positive values for sigma (numeric vector)
seed	single value, interpreted as an in integer, used to initialize the random number generation state

Details

The average intra-donor pool variance is described in (Imbert et al., 2018).

Value

a data frame with the values of sigma and the corresponding intra-donor pool variances

Author(s)

Alyssa Imbert, [e-mail]

Nathalie Vialaneix, [e-mail]

References

Imbert, A., Valsesia, A., Le Gall, C., Armenise, C., Lefebvre, G. Gourraud, P.A., Viguerie, N. and Villa-Vialaneix, N. (2018) Multiple hot-deck imputation for network inference from RNA sequencing data. Bioinformatics. doi: 10.1093/bioinformatics/btx819.

See Also

varIntra

Examples

data(lung)
data(thyroid)
nobs <- nrow(lung)
miss_ind <- sample(1:nobs, round(0.2 * nobs), replace = FALSE)
lung[miss_ind, ] <- NA
lung <- na.omit(lung)
sigma_stats <- chooseSigma(lung, thyroid, 1:5)
## Not run: plot(sigma_stats, type = "b")

RNAseqNet documentation built on July 2, 2020, 4:15 a.m.