Nothing
R/pdBuilderV2TiledRegion.R
In pdInfoBuilder: Platform Design Information Package Builder
Defines functions
parseNgsTrio
## The following tables will be available:
## pmfeature: fid, fsetid, chrom, location, x, y
## featureSet: fsetid (region name), chrom, start, end
## mmfeature (opt): fid, fid (matching pm), x, y
## bgfeature: fid, x, y
#######################################################################
## SECTION A - Db Schema
#######################################################################
tiledRegionFeatureSetSchema <- list(col2type=c(
fsetid="INTEGER",
man_fsetid="TEXT",
chrom="TEXT",
start="INTEGER",
end="INTEGER"),
col2key=c(
fsetid="PRIMARY KEY"
))
tiledRegionPmFeatureSchema <- list(col2type=c(
fid="INTEGER",
fsetid="INTEGER",
position="INTEGER",
x="INTEGER",
y="INTEGER",
type="TEXT"),
col2key=c(
fid="PRIMARY KEY"
))
## TODO: tiledRegionMmFeatureSchema
tiledRegionMmFeatureSchema <- NULL
tiledRegionBgFeatureSchema <- list(col2type=c(
fid="INTEGER",
fsetid="INTEGER",
x="INTEGER",
y="INTEGER",
type="INTEGER"
),
col2key=c(
fid="PRIMARY KEY"
))
#######################################################################
## SECTION B - Utils - This should be moved from here
## as everything in this section can be used on other cases
#######################################################################
#######################################################################
## SECTION C - Parser specific for NGS Tiled Regions
## This will take NDF/POS/XYS trio and process (in memory)
## the data, generating data.frames for each table
## (featureSet, pmfeature, mmfeature*, bgfeature**)
## to be created in the db.
#######################################################################
parseNgsTrio <- function(ndfFile, posFile, xysFile, verbose=TRUE){
stopifnot(!missing(ndfFile), !missing(posFile), !missing(xysFile))
#######################################################################
## Step 1: Parse NDF
#######################################################################
if (verbose) msgParsingFile(ndfFile)
optNrows <- getOption("pdInfoBuilder_NROWS")
if (is.null(optNrows))
optNrows <- 1000
tmp <- read.delim(ndfFile, stringsAsFactors=FALSE, nrow=optNrows)
ndfdata <- read.delim(ndfFile, stringsAsFactors=FALSE, colClasses=sapply(tmp, class))
rm(tmp)
if (verbose) msgOK()
ndfdata[["fsetid"]] <- as.integer(as.factor(ndfdata[["SEQ_ID"]]))
#######################################################################
## Step 2: Parse POS
#######################################################################
if (verbose) msgParsingFile(posFile)
posdata <- read.delim(posFile, stringsAsFactors=FALSE)
posdata <- posdata[!duplicated(posdata),]
rownames(posdata) <- NULL
if (verbose) msgOK()
#######################################################################
## Step 3: Match POS and NDF
## and update positional info
#######################################################################
if (verbose) simpleMessage("Merging NDF and POS files... ")
ndfdata <- merge(ndfdata, posdata, by.x=c("SEQ_ID", "PROBE_ID"), by.y=c("SEQ_ID", "PROBE_ID"), all.x=TRUE)
if (all(c("POSITION.x", "POSITION.y") %in% names(ndfdata))){
ndfdata[["POSITION"]] <- ndfdata[["POSITION.y"]]
ndfdata[["POSITION.x"]] <- ndfdata[["POSITION.y"]] <- NULL
}
rm(posdata)
if (verbose) msgOK()
#######################################################################
## Step 3.1: Get XYS files and remove all controls (ie, NA in XYS)
#######################################################################
if (verbose) msgParsingFile(xysFile)
xysdata <- read.delim(xysFile, comment.char="#")
if (verbose) msgOK()
xysdata[["fid"]] <- 1:nrow(xysdata)
ndfdata <- merge(ndfdata, xysdata, by.x=c("X", "Y"), by.y=c("X", "Y"))
controls <- which(is.na(ndfdata[["SIGNAL"]]))
ndfdata <- ndfdata[-controls,]
rm(controls)
#######################################################################
## Step 4: Prepare contents for featureSet table
## Fields featureSet: man_fsetid, chrom, start, end, type
#######################################################################
theMin <- aggregate(ndfdata[["POSITION"]], by=list(SEQ_ID=ndfdata[["SEQ_ID"]]), min)
names(theMin) <- c("man_fsetid", "start")
theMax <- aggregate(ndfdata[["POSITION"]], by=list(SEQ_ID=ndfdata[["SEQ_ID"]]), max)
names(theMax) <- c("man_fsetid", "end")
featureSet <- merge(theMin, theMax)
rm(theMin, theMax)
dups <- duplicated(ndfdata[["SEQ_ID"]])
featureSet <- merge(featureSet,
ndfdata[!dups, c("SEQ_ID", "CHROMOSOME", "fsetid")],
by.x="man_fsetid", by.y="SEQ_ID")
names(featureSet) <- c("man_fsetid", "start", "end", "chrom", "fsetid")
featureSet <- featureSet[, c("fsetid", "man_fsetid", "chrom", "start", "end")]
rm(dups)
#######################################################################
## Step 5: Prepare contents for pmfeature, mmfeature and bgfeature
## Fields pmfeature: fid, fsetid, position, x, y
## mmfeature: fid, fsetid, position, x, y, fid(PM)
## bgfeature: fid, fsetid, x, y
## FIX ME: Need to check the selection for BG probes
## Implement mmfeature
## Comments: ideally, the tables would be ordered by chrom+position;
## but 'fid' is the PRIMARY KEY, and the table will be
## ordered by that
#######################################################################
features <- ndfdata[, c("X", "Y", "fsetid", "POSITION", "MISMATCH",
"MATCH_INDEX", "CONTAINER", "CHROMOSOME",
"PROBE_SEQUENCE", "fid", "PROBE_CLASS",
"CONTAINER")]
names(features) <- c("x", "y", "fsetid", "position", "mismatch",
"match_index", "container", "chromosome",
"sequence", "fid", "class", "type")
geometry <- paste(max(ndfdata[["Y"]]), max(ndfdata[["X"]]), sep=";")
rm(xysdata, ndfdata)
## FIX ME: Double check ordering
features <- features[order(features[["chromosome"]], features[["position"]]),]
## FIX ME: This should be passed by function
experimentalIDs <- "experimental"
pmFeatures <- subset(features, features$mismatch == 0 & class %in% experimentalIDs)[, c("fid", "fsetid", "position", "x", "y", "type")]
pmSequence <- subset(features, features$mismatch == 0 & class %in% experimentalIDs)[, c("fid", "sequence")]
pmSequence <- pmSequence[order(pmSequence[["fid"]]),]
pmSequence <- DataFrame(fid=pmSequence[["fid"]],
sequence=DNAStringSet(pmSequence[["sequence"]]))
mmFeatures <- subset(features, features$mismatch > 0 & class %in% experimentalIDs)
## add mmSequence
if (any(mmFeatures[["mismatch"]] >= 10000))
stop("Control probe possibly identified as Experimental")
if (nrow(mmFeatures) > 0)
stop("Add methods for MMs")
rm(mmFeatures)
bgFeatures <- subset(features, !(class %in% experimentalIDs))[, c("fid", "fsetid", "x", "y", "type")]
bgSequence <- subset(features, !(class %in% experimentalIDs))[, c("fid", "sequence")]
bgSequence <- bgSequence[order(bgSequence[["fid"]]),]
bgSequence <- DataFrame(fid=bgSequence[["fid"]],
sequence=DNAStringSet(bgSequence[["sequence"]]))
rm(features, experimentalIDs)
return(list(featureSet=featureSet, pmFeatures=pmFeatures,
bgFeatures=bgFeatures, geometry=geometry,
pmSequence=pmSequence, bgSequence=bgSequence))
}
#######################################################################
## SECTION D - Package Maker
## This shouldn't be extremely hard.
## The idea is to: i) get array info (name, pkgname, dbname)
## ii) parse data; iii) create pkg from template;
## iv) dump the database
#######################################################################
setMethod("makePdInfoPackage", "NgsTilingPDInfoPkgSeed",
function(object, destDir=".", batch_size=10000, quiet=FALSE, unlink=FALSE) {
msgBar()
message("Building annotation package for Nimblegen Tiling Array")
message("NDF: ", basename(object@ndfFile))
message("POS: ", basename(object@posFile))
message("XYS: ", basename(object@xysFile))
msgBar()
#######################################################################
## Part i) get array info (chipName, pkgName, dbname)
#######################################################################
chip <- chipName(object)
pkgName <- cleanPlatformName(chip)
extdataDir <- file.path(destDir, pkgName, "inst", "extdata")
dbFileName <- paste(pkgName, "sqlite", sep=".")
dbFilePath <- file.path(extdataDir, dbFileName)
#######################################################################
## Part ii) parse data. This should return a list of data.frames.
## The names of the elements in the list are table names.
#######################################################################
parsedData <- parseNgsTrio(object@ndfFile,
object@posFile,
object@xysFile,
verbose=!quiet)
#######################################################################
## Part iii) Create package from template
#######################################################################
syms <- list(MANUF=object@manufacturer,
VERSION=object@version,
GENOMEBUILD=object@genomebuild,
AUTHOR=object@author,
AUTHOREMAIL=object@email,
LIC=object@license,
DBFILE=dbFileName,
CHIPNAME=chip,
PKGNAME=pkgName,
PDINFONAME=pkgName,
PDINFOCLASS="NgsTilingPDInfo",
GEOMETRY=parsedData[["geometry"]])
templateDir <- system.file("pd.PKG.template",
package="pdInfoBuilder")
createPackage(pkgname=pkgName, destinationDir=destDir,
originDir=templateDir, symbolValues=syms,
quiet=quiet)
dir.create(extdataDir, recursive=TRUE)
#######################################################################
## Part iv) Create SQLite database
## FIX ME: Trusting tiledRegionFeatureSetSchema will be visible from
## inside the method;
## Fix ordering of the tables
#######################################################################
conn <- dbConnect(dbDriver("SQLite"), dbname=dbFilePath)
increaseDbPerformance(conn)
dbCreateTable(conn,
"featureSet",
tiledRegionFeatureSetSchema[["col2type"]],
tiledRegionFeatureSetSchema[["col2key"]])
dbCreateTable(conn,
"pmfeature",
tiledRegionPmFeatureSchema[["col2type"]],
tiledRegionPmFeatureSchema[["col2key"]])
containsMm <- "mmFeatures" %in% names(parsedData)
if (containsMm)
dbCreateTable(conn,
"mmfeature",
tiledRegionMmFeatureSchema[["col2type"]],
tiledRegionMmFeatureSchema[["col2key"]])
dbCreateTable(conn,
"bgfeature",
tiledRegionBgFeatureSchema[["col2type"]],
tiledRegionBgFeatureSchema[["col2key"]])
dbInsertDataFrame(conn, "featureSet", parsedData[["featureSet"]],
tiledRegionFeatureSetSchema[["col2type"]], !quiet)
dbInsertDataFrame(conn, "pmfeature", parsedData[["pmFeatures"]],
tiledRegionPmFeatureSchema[["col2type"]], !quiet)
if (containsMm)
dbInsertDataFrame(conn, "mmfeature", parsedData[["mmFeatures"]],
tiledRegionMmFeatureSchema[["col2type"]], !quiet)
dbInsertDataFrame(conn, "bgfeature", parsedData[["bgFeatures"]],
tiledRegionBgFeatureSchema[["col2type"]], !quiet)
dbCreateTableInfo(conn, !quiet)
## Create indices
dbCreateIndicesBg(conn, !quiet)
dbCreateIndicesPm(conn, !quiet)
dbCreateIndicesFs(conn, !quiet)
dbGetQuery(conn, "VACUUM")
dbDisconnect(conn)
#######################################################################
## Part v) Save sequence DataFrames
## FIX ME: Fix ordering of the tables to match xxFeature tables
#######################################################################
datadir <- file.path(destDir, pkgName, "data")
dir.create(datadir)
pmSequence <- parsedData[["pmSequence"]]
bgSequence <- parsedData[["bgSequence"]]
pmSeqFile <- file.path(datadir, "pmSequence.rda")
bgSeqFile <- file.path(datadir, "bgSequence.rda")
if (!quiet) message("Saving DataFrame object for PM.")
save(pmSequence, file=pmSeqFile, compress='xz')
if (!quiet) message("Saving DataFrame object for BG.")
save(bgSequence, file=bgSeqFile, compress='xz')
if (!quiet) message("Done.")
})
Try the pdInfoBuilder package in your browser
Any scripts or data that you put into this service are public.
pdInfoBuilder documentation built on Nov. 8, 2020, 5:19 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions parseNgsTrio
## The following tables will be available:
## pmfeature: fid, fsetid, chrom, location, x, y
## featureSet: fsetid (region name), chrom, start, end
## mmfeature (opt): fid, fid (matching pm), x, y
## bgfeature: fid, x, y
#######################################################################
## SECTION A - Db Schema
#######################################################################
tiledRegionFeatureSetSchema <- list(col2type=c(
fsetid="INTEGER",
man_fsetid="TEXT",
chrom="TEXT",
start="INTEGER",
end="INTEGER"),
col2key=c(
fsetid="PRIMARY KEY"
))
tiledRegionPmFeatureSchema <- list(col2type=c(
fid="INTEGER",
fsetid="INTEGER",
position="INTEGER",
x="INTEGER",
y="INTEGER",
type="TEXT"),
col2key=c(
fid="PRIMARY KEY"
))
## TODO: tiledRegionMmFeatureSchema
tiledRegionMmFeatureSchema <- NULL
tiledRegionBgFeatureSchema <- list(col2type=c(
fid="INTEGER",
fsetid="INTEGER",
x="INTEGER",
y="INTEGER",
type="INTEGER"
),
col2key=c(
fid="PRIMARY KEY"
))
#######################################################################
## SECTION B - Utils - This should be moved from here
## as everything in this section can be used on other cases
#######################################################################
#######################################################################
## SECTION C - Parser specific for NGS Tiled Regions
## This will take NDF/POS/XYS trio and process (in memory)
## the data, generating data.frames for each table
## (featureSet, pmfeature, mmfeature*, bgfeature**)
## to be created in the db.
#######################################################################
parseNgsTrio <- function(ndfFile, posFile, xysFile, verbose=TRUE){
stopifnot(!missing(ndfFile), !missing(posFile), !missing(xysFile))
#######################################################################
## Step 1: Parse NDF
#######################################################################
if (verbose) msgParsingFile(ndfFile)
optNrows <- getOption("pdInfoBuilder_NROWS")
if (is.null(optNrows))
optNrows <- 1000
tmp <- read.delim(ndfFile, stringsAsFactors=FALSE, nrow=optNrows)
ndfdata <- read.delim(ndfFile, stringsAsFactors=FALSE, colClasses=sapply(tmp, class))
rm(tmp)
if (verbose) msgOK()
ndfdata[["fsetid"]] <- as.integer(as.factor(ndfdata[["SEQ_ID"]]))
#######################################################################
## Step 2: Parse POS
#######################################################################
if (verbose) msgParsingFile(posFile)
posdata <- read.delim(posFile, stringsAsFactors=FALSE)
posdata <- posdata[!duplicated(posdata),]
rownames(posdata) <- NULL
if (verbose) msgOK()
#######################################################################
## Step 3: Match POS and NDF
## and update positional info
#######################################################################
if (verbose) simpleMessage("Merging NDF and POS files... ")
ndfdata <- merge(ndfdata, posdata, by.x=c("SEQ_ID", "PROBE_ID"), by.y=c("SEQ_ID", "PROBE_ID"), all.x=TRUE)
if (all(c("POSITION.x", "POSITION.y") %in% names(ndfdata))){
ndfdata[["POSITION"]] <- ndfdata[["POSITION.y"]]
ndfdata[["POSITION.x"]] <- ndfdata[["POSITION.y"]] <- NULL
}
rm(posdata)
if (verbose) msgOK()
#######################################################################
## Step 3.1: Get XYS files and remove all controls (ie, NA in XYS)
#######################################################################
if (verbose) msgParsingFile(xysFile)
xysdata <- read.delim(xysFile, comment.char="#")
if (verbose) msgOK()
xysdata[["fid"]] <- 1:nrow(xysdata)
ndfdata <- merge(ndfdata, xysdata, by.x=c("X", "Y"), by.y=c("X", "Y"))
controls <- which(is.na(ndfdata[["SIGNAL"]]))
ndfdata <- ndfdata[-controls,]
rm(controls)
#######################################################################
## Step 4: Prepare contents for featureSet table
## Fields featureSet: man_fsetid, chrom, start, end, type
#######################################################################
theMin <- aggregate(ndfdata[["POSITION"]], by=list(SEQ_ID=ndfdata[["SEQ_ID"]]), min)
names(theMin) <- c("man_fsetid", "start")
theMax <- aggregate(ndfdata[["POSITION"]], by=list(SEQ_ID=ndfdata[["SEQ_ID"]]), max)
names(theMax) <- c("man_fsetid", "end")
featureSet <- merge(theMin, theMax)
rm(theMin, theMax)
dups <- duplicated(ndfdata[["SEQ_ID"]])
featureSet <- merge(featureSet,
ndfdata[!dups, c("SEQ_ID", "CHROMOSOME", "fsetid")],
by.x="man_fsetid", by.y="SEQ_ID")
names(featureSet) <- c("man_fsetid", "start", "end", "chrom", "fsetid")
featureSet <- featureSet[, c("fsetid", "man_fsetid", "chrom", "start", "end")]
rm(dups)
#######################################################################
## Step 5: Prepare contents for pmfeature, mmfeature and bgfeature
## Fields pmfeature: fid, fsetid, position, x, y
## mmfeature: fid, fsetid, position, x, y, fid(PM)
## bgfeature: fid, fsetid, x, y
## FIX ME: Need to check the selection for BG probes
## Implement mmfeature
## Comments: ideally, the tables would be ordered by chrom+position;
## but 'fid' is the PRIMARY KEY, and the table will be
## ordered by that
#######################################################################
features <- ndfdata[, c("X", "Y", "fsetid", "POSITION", "MISMATCH",
"MATCH_INDEX", "CONTAINER", "CHROMOSOME",
"PROBE_SEQUENCE", "fid", "PROBE_CLASS",
"CONTAINER")]
names(features) <- c("x", "y", "fsetid", "position", "mismatch",
"match_index", "container", "chromosome",
"sequence", "fid", "class", "type")
geometry <- paste(max(ndfdata[["Y"]]), max(ndfdata[["X"]]), sep=";")
rm(xysdata, ndfdata)
## FIX ME: Double check ordering
features <- features[order(features[["chromosome"]], features[["position"]]),]
## FIX ME: This should be passed by function
experimentalIDs <- "experimental"
pmFeatures <- subset(features, features$mismatch == 0 & class %in% experimentalIDs)[, c("fid", "fsetid", "position", "x", "y", "type")]
pmSequence <- subset(features, features$mismatch == 0 & class %in% experimentalIDs)[, c("fid", "sequence")]
pmSequence <- pmSequence[order(pmSequence[["fid"]]),]
pmSequence <- DataFrame(fid=pmSequence[["fid"]],
sequence=DNAStringSet(pmSequence[["sequence"]]))
mmFeatures <- subset(features, features$mismatch > 0 & class %in% experimentalIDs)
## add mmSequence
if (any(mmFeatures[["mismatch"]] >= 10000))
stop("Control probe possibly identified as Experimental")
if (nrow(mmFeatures) > 0)
stop("Add methods for MMs")
rm(mmFeatures)
bgFeatures <- subset(features, !(class %in% experimentalIDs))[, c("fid", "fsetid", "x", "y", "type")]
bgSequence <- subset(features, !(class %in% experimentalIDs))[, c("fid", "sequence")]
bgSequence <- bgSequence[order(bgSequence[["fid"]]),]
bgSequence <- DataFrame(fid=bgSequence[["fid"]],
sequence=DNAStringSet(bgSequence[["sequence"]]))
rm(features, experimentalIDs)
return(list(featureSet=featureSet, pmFeatures=pmFeatures,
bgFeatures=bgFeatures, geometry=geometry,
pmSequence=pmSequence, bgSequence=bgSequence))
}
#######################################################################
## SECTION D - Package Maker
## This shouldn't be extremely hard.
## The idea is to: i) get array info (name, pkgname, dbname)
## ii) parse data; iii) create pkg from template;
## iv) dump the database
#######################################################################
setMethod("makePdInfoPackage", "NgsTilingPDInfoPkgSeed",
function(object, destDir=".", batch_size=10000, quiet=FALSE, unlink=FALSE) {
msgBar()
message("Building annotation package for Nimblegen Tiling Array")
message("NDF: ", basename(object@ndfFile))
message("POS: ", basename(object@posFile))
message("XYS: ", basename(object@xysFile))
msgBar()
#######################################################################
## Part i) get array info (chipName, pkgName, dbname)
#######################################################################
chip <- chipName(object)
pkgName <- cleanPlatformName(chip)
extdataDir <- file.path(destDir, pkgName, "inst", "extdata")
dbFileName <- paste(pkgName, "sqlite", sep=".")
dbFilePath <- file.path(extdataDir, dbFileName)
#######################################################################
## Part ii) parse data. This should return a list of data.frames.
## The names of the elements in the list are table names.
#######################################################################
parsedData <- parseNgsTrio(object@ndfFile,
object@posFile,
object@xysFile,
verbose=!quiet)
#######################################################################
## Part iii) Create package from template
#######################################################################
syms <- list(MANUF=object@manufacturer,
VERSION=object@version,
GENOMEBUILD=object@genomebuild,
AUTHOR=object@author,
AUTHOREMAIL=object@email,
LIC=object@license,
DBFILE=dbFileName,
CHIPNAME=chip,
PKGNAME=pkgName,
PDINFONAME=pkgName,
PDINFOCLASS="NgsTilingPDInfo",
GEOMETRY=parsedData[["geometry"]])
templateDir <- system.file("pd.PKG.template",
package="pdInfoBuilder")
createPackage(pkgname=pkgName, destinationDir=destDir,
originDir=templateDir, symbolValues=syms,
quiet=quiet)
dir.create(extdataDir, recursive=TRUE)
#######################################################################
## Part iv) Create SQLite database
## FIX ME: Trusting tiledRegionFeatureSetSchema will be visible from
## inside the method;
## Fix ordering of the tables
#######################################################################
conn <- dbConnect(dbDriver("SQLite"), dbname=dbFilePath)
increaseDbPerformance(conn)
dbCreateTable(conn,
"featureSet",
tiledRegionFeatureSetSchema[["col2type"]],
tiledRegionFeatureSetSchema[["col2key"]])
dbCreateTable(conn,
"pmfeature",
tiledRegionPmFeatureSchema[["col2type"]],
tiledRegionPmFeatureSchema[["col2key"]])
containsMm <- "mmFeatures" %in% names(parsedData)
if (containsMm)
dbCreateTable(conn,
"mmfeature",
tiledRegionMmFeatureSchema[["col2type"]],
tiledRegionMmFeatureSchema[["col2key"]])
dbCreateTable(conn,
"bgfeature",
tiledRegionBgFeatureSchema[["col2type"]],
tiledRegionBgFeatureSchema[["col2key"]])
dbInsertDataFrame(conn, "featureSet", parsedData[["featureSet"]],
tiledRegionFeatureSetSchema[["col2type"]], !quiet)
dbInsertDataFrame(conn, "pmfeature", parsedData[["pmFeatures"]],
tiledRegionPmFeatureSchema[["col2type"]], !quiet)
if (containsMm)
dbInsertDataFrame(conn, "mmfeature", parsedData[["mmFeatures"]],
tiledRegionMmFeatureSchema[["col2type"]], !quiet)
dbInsertDataFrame(conn, "bgfeature", parsedData[["bgFeatures"]],
tiledRegionBgFeatureSchema[["col2type"]], !quiet)
dbCreateTableInfo(conn, !quiet)
## Create indices
dbCreateIndicesBg(conn, !quiet)
dbCreateIndicesPm(conn, !quiet)
dbCreateIndicesFs(conn, !quiet)
dbGetQuery(conn, "VACUUM")
dbDisconnect(conn)
#######################################################################
## Part v) Save sequence DataFrames
## FIX ME: Fix ordering of the tables to match xxFeature tables
#######################################################################
datadir <- file.path(destDir, pkgName, "data")
dir.create(datadir)
pmSequence <- parsedData[["pmSequence"]]
bgSequence <- parsedData[["bgSequence"]]
pmSeqFile <- file.path(datadir, "pmSequence.rda")
bgSeqFile <- file.path(datadir, "bgSequence.rda")
if (!quiet) message("Saving DataFrame object for PM.")
save(pmSequence, file=pmSeqFile, compress='xz')
if (!quiet) message("Saving DataFrame object for BG.")
save(bgSequence, file=bgSeqFile, compress='xz')
if (!quiet) message("Done.")
})
Try the pdInfoBuilder package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.