Description Usage Arguments Value NOTE Author(s) See Also Examples
Descriptive statistics on intergenic distance data
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GeneSetDistances |
A |
confLevel |
Confidence level between 0 and 1. |
nboot |
Integer (Default to 1e4). Number of bootstrap samples. |
CItype |
Type of confidence interval ("bca" or "perc"). |
ncores |
Number of cores to use for boostrap. |
A tibble with the following columns:
GeneSet. Name of the gene set.
Side. Upstream or Downstream.
Orientation. Orientation of the neighbor (SameStrand or OppositeStrand).
n. Number of observations.
Min. Minimum distance.
Q1. First quartile.
Median.
Median_LowerCI. Lower bound of the median bootstrap confidence interval.
Median_UpperCI. Upper bound of the median bootstrap confidence interval.
Mean.
Mean_LowerCI. Lower bound of the mean bootstrap confidence interval.
Mean_UpperCI. Upper bound of the mean bootstrap confidence interval.
Q3. Third quartile.
Max. Maximum distance.
SD. Standard deviation.
SEM. Standard Error of the Mean.
When nboot is too small and CItype=="bca", the following error can occur: "estimated adjustment 'a' is NA" In this case, use CItype="perc" and/or increase nboot. Using nboot >= 1e4 (the default) is always recommended.
Pascal GP Martin
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## Obtain gene neighborhood information:
GeneNeighbors <- getGeneNeighborhood(Genegr)
## Get a (random) set of (100) genes:
set.seed(123)
randGenes <- sample(names(Genegr), 100)
## Extract distances for this set of genes and for all genes :
myGeneSets <- list("RandomGenes" = randGenes,
"AllGenes" = GeneNeighbors$GeneName)
distForGeneSets <- dist2Neighbors(GeneNeighbors,
myGeneSets)
## Obtain descriptive statistics for these sets of genes:
distStats(distForGeneSets,
nboot = 1e3, CItype = "perc", ncores = 1)
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