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library(Gviz)
library(biomaRt)
library(Biobase)
library(rtracklayer)
library(RMySQL)
fetchAllGenomesFromUcsc <- function() {
mydb <- dbConnect(MySQL(), user="genome", dbname="hgcentral",
host="genome-mysql.cse.ucsc.edu")
rs <- dbSendQuery(mydb, "select * from dbDb")
out <- fetch(rs, n=-1)
## rs2 <- dbSendQuery(mydb, "select * from dbDbArch")
## out2 <- fetch(rs2, n=-1)
out <- out[out$active!=0, ] # only active
cols <- c("name", "description", "organism", "scientificName",
"sourceName","taxId", "orderKey") # smallest orderKey == rescent
out <- out[, cols]
out <- out[order(out$organism, out$orderKey),]
## out <- split(out, out$organism)
return(out)
}
testBiomartVersion <- function() {
allGenomes <- union(read.delim(system.file(package="Gviz", "extdata/biomartVersionsLatest.txt"))$ucscId,
read.delim(system.file(package="Gviz", "extdata/biomartVersionsNow.txt"))$ucscId)
res <- mclapply(allGenomes, function(genome){
return(try({
map <- Gviz:::.ucsc2Ensembl(genome)
res <- list()
if(map$date == "head"){
bm <- useMart("ensembl", dataset=map$dataset)
ds <- listDatasets(bm)
mt <- ds[match(map$dataset, ds$dataset), "version"]
if(is.na(mt)){
res <- list(current=genome, set=map$dataset, type="head", cause="error")
}
if(mt != map$value){
res <- list(current=genome, set=map$value, setCurrent=mt, type="head", cause="mismatch")
}
}else{
bm <- useMart(host=sprintf("%s.archive.ensembl.org", tolower(sub(".", "", map$date, fixed=TRUE))),
biomart="ENSEMBL_MART_ENSEMBL", dataset=map$dataset)
ds <- listDatasets(bm)
mt <- ds[match(map$dataset, ds$dataset), "version"]
if(is.na(mt)){
res <- list(current=genome, set=map$dataset, type="archive", cause="error")
}
if(mt != map$value){
res <- list(current=genome, set=map$value, setArchive=sub(".", " ", map$date, fixed=TRUE),
setVersion=map$version, setCurrent=mt, type="archive", cause="mismatch")
}
}
res
}, silent=TRUE))
})
res <- res[listLen(res)>0]
res[sapply(res, is, "try-error")] <- list(type="error")
allFields <- unique(unlist(lapply(res, names)))
dt <- as.data.frame(do.call(rbind, lapply(res, function(x) t(as.data.frame(unlist(x)[allFields])))),
stringsAsFactors=FALSE)
rownames(dt) <- NULL
gens <- ucscGenomes()
gens$version <- as.numeric(gsub("[a-zA-Z]*", "", gens$db))
gensS <- split(gens, gsub("[0-9]*$", "", gens$db))
highestVersion <- as.data.frame(t(sapply(gensS, function(x) unlist(x[which.max(x$version),]))),
stringsAsFactors=FALSE)
rownames(gens) <- gens$db
mt <- match(gsub("[0-9]*$", "", dt$current), rownames(highestVersion))
tmp <- highestVersion[mt, c("db", "date", "name", "version")]
colnames(tmp) <- paste("UCSCLatest", colnames(tmp), sep="_")
dt2 <- cbind(dt, tmp)
tmp2 <- gens[dt2$current,c("db", "date", "name", "version")]
colnames(tmp2) <- paste("UCSC", colnames(tmp2), sep="_")
dt3 <- cbind(dt2, tmp2)
dt3 <- dt3[rowSums(is.na(dt3)) < ncol(dt3),]
if(require(writexl)) {
write_xlsx(list("Sheet1"=dt3), path="ensMappings.xlsx")
}
write.table(dt3, file="ensMappings.txt", sep="\t", quote=FALSE)
return(dt3)
}
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