sharedness: Sharedness Score
In pmm: Parallel Mixed Model

Description Usage Arguments Details Value Author(s) Examples

View source: R/sharedness.R

The sharedness score computes the strength of sharedness of hit genes among the conditions.

1	sharedness(fit, threshold = 0.2, na.action = "na.omit")

`fit`	data frame returned by the `pmm` function.
`threshold`	threshold for the false discovery rate. Genes are counted as hits if they are below this threshold. Default is 0.2.
`na.action`	a function that indicates what happens if `fit` contains NAs. There are two options: "na.omit" (default) or "use". In the case of "na.omit" the sharedness score is applied to `na.omit(fit)` and in the other case the sharedness score is adapted for each gene to the number of conditions without NA.

The sharedness score is a combination of two quantities:

sh_g = 1/2 ( (1 - mean(fdr_cg)) + sum (fdr_cg < 1) )

The first part defines the shift away from 1 and the second part describes how many pathogens support the shift (proportion of FDRs < 1).

The score returns a value between 0 and 1 for each gene. Score 0 indicates that a gene is not shared among the condition and score 1 that the gene is significant among all conditions.

Anna Drewek <adrewek@stat.math.ethz.ch>

data(kinome)
fit <- pmm(kinome,"InfectionIndex","weight_library")
sh <- sharedness(fit, threshold = 0.2)
head(sh)

## NA-Handling
kinome$InfectionIndex[kinome$GeneID == 132158 & kinome$condition ==
"ADENO"] <- rep(NA,12)
fit <- pmm(kinome,"InfectionIndex","weight_library")
## Sharedness score for genes present in all conditions
sh <- sharedness(fit, threshold = 0.2, na.action = "na.omit")
head(sh)
## Sharedness score for all significant genes
sh <- sharedness(fit, threshold = 0.2, na.action = "use")
head(sh)