orderedIntersect: orderedIntersect
In zhushijia/GIGSEA: Genotype Imputed Gene Set Enrichment Analysis

Description Usage Arguments Value Author(s) Examples

orderedIntersect sorts a data frame based on a given collumn and intersects with another vector.

1	orderedIntersect(x, by.x, by.y, duplicate = "mean")

`x`	a data frame comprising of numeric values
`by.x`	a vector of character values. The data frame is sorted based on by.x
`by.y`	a vector of character values. After being sorted, the rows of x are further filtered by intersecting by.x with by.y
`duplicate`	a character value taking values from "mean", "median", "max", "max", "min", and "remove". It represents how to deal with the duplicates in x in terms of by.x.

a data frame sorted by "by.x" and intersected with "by.y"

Shijia Zhu, shijia.zhu@mssm.edu

# load data
data(heart.metaXcan)
gene <- heart.metaXcan$gene_name

# extract the imputed Z-score of gene differential expression, which follows 
# normal distribution
fc <- heart.metaXcan$zscore

# use the prediction R^2 and fraction of imputation-used SNPs as weights
usedFrac <- heart.metaXcan$n_snps_used / heart.metaXcan$n_snps_in_cov
r2 <- heart.metaXcan$pred_perf_r2
weights <- usedFrac*r2

# build a new data frame for the following weighted linear regression-based 
# enrichment analysis
data <- data.frame(gene,fc,weights)
head(data)

net <- MSigDB.KEGG.Pathway$net

# intersect the user-provided imputed genes with the gene set of interest
data2 <- orderedIntersect( x=data[,c("fc","weights")], 
by.x=data$gene, by.y=rownames(net) )
net2 <- orderedIntersect( x=net, by.x=rownames(net), by.y=data$gene )
all( rownames(net2) == rownames(data2) )