R/rnaCrosslinkDataSet.R
In JLP-BioInf/comradesOO: Analysis of RNA Crosslinking Data
Defines functions
rnaCrosslinkDataSet
Documented in
rnaCrosslinkDataSet
#' @include rnaCrosslinkOO.R
#' rnaCrosslinkDataSet
#'
#' An S4 class to represent a rnaCrosslink dataset
#' @rdname rnaCrosslinkDataSet
#' @export
#'
setClass(
"rnaCrosslinkDataSet",
slots = c(
rnas = "character",
rnaSize = "numeric",
sampleTable = "data.frame",
# meta data
InputFiles = "list",
# data tables
matrixList = "list",
clusterGrangesList = "list",
clusterTableList = "list",
clusterTableFolded = "data.frame",
interactionTable = "data.frame",
viennaStructures = "list",
dgs = "list"
),
prototype = list()
)
setValidity("rnaCrosslinkDataSet", function(object) {
})
#' rnaCrosslinkDataSet
#'
#' \code{rnaCrosslinkDataSet} objects are used to store the input meta-data, data and
#' create a framework for the storage of results. Whilst creating the object,
#' the original Input files are also filtered for the RNA of interest. Check the
#' package vignette for more information.
#'
#'
#' @param rnas vector - The names of the RNA interest, these must be displayed
#' the same way as in the input Input Files.
#' @param rnaSize named list - The sizes (nt) of the RNAs of interest, the list
#' elements must have same names as the \code{rnas} vector and each each contain
#' one numeric value.
#' @param sampleTable string - The address of the sample table, the sample table
#' must have 4 columns, fileName (the full path and file name of the input
#' Input file for each sample ), group ("s" - sample or "c" - control),
#' sample (1,2,3, etc), sampleName (must be unique).
#' @param subset a vector of 4 values to subset based on structural read size. c(l-min,l-max,r-min,r-max)
#' @param sample The number of reads to sample for each sample.
#'
#' @return A rnaCrosslinkDataSet object.
#'
#'
#'
#' @slot clusterTableFolded table - a table similar to the \code{clusterTableList}
#' it contains coordinates of the clusters along with vienna format fold and
#' RNA sequences for each cluster
#' @slot clusterTableList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. contains a table
#' with coordinates and information about the clusters identified
#' @slot clusterGrangesList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. contains GRanges
#' objects of the original duplexes with their cluster membership
#' @slot sampleTable table - Column names; fileName, group (s or c),
#' sample (1,2,3, etc), sampleName (must be unique)
#' @slot rnas string - a single RNA to analyse - must be present in \code{rnas(cdsObject)}
#' @slot rnaSize if set to 0 this will be calculated
#' @slot matrixList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. Contains a set
#' of contact matrices, each cell contains the number of duplexes identified
#' for position x,y.
#' @slot InputFiles List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{InputFiles(cds)[[rna]][[type]][[sample]]}. Contains a set of
#' tables, these are the original Input files that were read in.
#' @slot interactionTable Table of interactions discovered in step1 of the folding
#' @slot viennaStructures List of vienna format structures from final prediction
#' @slot dgs List of free energies
#'
#' @name rnaCrosslinkDataSet
#' @docType class
#' @rdname rnaCrosslinkDataSet
#'
#' @examples
#' # make example input
#' cds = makeExamplernaCrosslinkDataSet()
#'
#'cds
#'
#' @export
rnaCrosslinkDataSet <- function(rnas,
rnaSize = 0 ,
sampleTable,
subset = "all",
sample = "all") {
###########################################################
# Read in the sample table
###########################################################
# check the inputs here, stop if wrong
message(" ******************************************** ")
message(" ***** rnaCrosslink-OO ****** ")
message(" ******************************************** ")
message(" *****-------*******************-------****** ")
message(" ***** Reading SampleTable ****** ")
# Read in sample table
#check for more than two samples
# if( nrow(sampleTable) < 2 ){
# stop( "The sample Table must contain at least 1
# sample and 1 control" )
# }
message(paste(" ***** Detected ",
nrow(sampleTable), " Samples ****** "))
###########################################################
#check column names of sampleTable
colnamesST = c("file", "group", "sample", "sampleName")
if (all(colnames(sampleTable) != colnamesST)) {
stop("Column names of metaData table should be :
file, group, sample, sampleNames")
}
# Get the comparison groups check group has the c and s
if (!(unique(as.character(sampleTable$group))[1] %in% c("c", "s") &
unique(as.character(sampleTable$group))[2] %in% c("c", "s"))) {
stop("Groups should be c and s")
}
# Make group into a list with control and sample
group = sampleTable[, "group"]
group2 = list()
group2[["c"]] = which(group == "c")
group2[["s"]] = which(group == "s")
group = group2
message(paste(
" ***** detected group c::",
paste(group[["c"]],
collapse = " ") ,
paste(rep(" ",
2),
collapse = ""),
" ***** "
))
message(paste(
" ***** detected group s::",
paste(group[["s"]],
collapse = " ") ,
paste(rep(" ",
(
2)),
collapse = ""),
" ***** "
))
###########################################################
# Get the sampleNames
sampleNames = c()
if (is.null(sampleTable$sampleName)) {
stop("The sample Table must have a column named sampleName")
} else if (length(unique(sampleTable$sampleName)) !=
length(sampleTable$sampleName)) {
stop("Sample names must be unique")
} else{
sampleNames = as.character(sampleTable$sampleName)
spaces = (length(sampleNames) * (3 - length(sampleNames))) * 2
if(spaces < 0 ){spaces = 0}
message(paste(
" **** ",
paste(rep(" ",
spaces,
collapse = ""),
" Sample Names: ",
paste(sampleNames, collapse = " "),
paste(rep(" ",
spaces,
collapse = ""),
" **** "
))))
}
###########################################################
# Read in the Input files
###########################################################
#load the files into a list
message(" ***** Reading Input Files ***** ")
InputFiles = list()
InputFiles[["all"]] = list()
InputFiles[["all"]][["all"]] = list()
# read in the tables
inputs <- lapply(as.character(sampleTable$file),
function(file)
read.table(file,colClasses = c("character",
"character",
"character",
"character",
"integer",
"integer",
"integer",
"integer",
"character",
"character",
"integer",
"integer",
"integer",
"integer",
"character")))
#check column names
if (all(sapply(inputs, function(file)
! (identical(
colnames(file),
c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
))))) {
stop(
" The input files do not look they are produced with the
nextflow pipeline, please check the documentation. "
)
}
#subset based on user options
message(" ***** Checking Subsetting Options ***** ")
if(length(subset) > 1){
if( (subset[1] > subset[2]) | (subset[3] > subset[4]) ){
stop("Subsetting options do not look right, min value is geater than max")
}
}
if(length(subset) == 1){
message(" ***** No user subsetting chosen ***** ")
}else{
message(paste(" ***** Subsetting ","leftMinMax = ",subset[1],
subset[2],
"RightMinMax = ",subset[3],
subset[4]," ***** "))
inputs <- lapply(inputs, function(x){
x = x[which( (c(x$V6 - x$V5) > subset[1] & c(x$V6 - x$V5) < subset[2]) &
(c(x$V14 - x$V13) > subset[3] & c(x$V14 - x$V13) < subset[4]) ),]
colnames(x) = c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
x
})
}
message(" ***** Checking Sampling Options ***** ")
if(sample == "all"){
message(" ***** No user sampling chosen ***** ")
}else{
message(paste(" ***** Sampling ",sample,
"Structural duplexes ***** "))
inputs <- lapply(inputs, function(x){
x = x[sample(1:nrow(x),size = sample,replace = F),]
colnames(x) = c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
x
})
}
checkRNA = function(inputs, rna) {
rnas %in% c(inputs$V4, inputs$V10)
}
rnaCheck = sapply(inputs, checkRNA, rna = rnas)
if(!any(rnaCheck)){
stop(
"No match for chosen RNA exists in this dataSet"
)
}
inputs = lapply(inputs, function(x) x[complete.cases(x),] )
inputs = lapply(inputs, function(x) x[!is.infinite(x$V8),] )
inputs = lapply(inputs, function(x) x[!is.infinite(x$V14),] )
InputFiles[["all"]][["all"]] = inputs
names(InputFiles[["all"]][["all"]]) = sampleNames
#get the maxpos
getMax = function(file, rna) {
return(max(file[file$V10 == rnas, "V14"],
max(file[file$V4 == rnas, "V8"])))
}
maxPos = max(sapply(inputs, getMax, rna = rnas))
###########################################################
message(" ***** Getting RNAs of Interest ****** ")
message(" ***** RNA of interest + Host RNA ***** ")
InputFiles[[rnas]][["original"]] = swapInputs(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
InputFiles[[rnas]][["host"]] = swapInputs3(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
message(" ***** RNA of interest Alone ***** ")
InputFiles[[rnas]][["noHost"]] = swapInputs2(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
###########################################################
# Make matrices of the specific RNA without host
###########################################################
message(" ***** Making Matrices ****** ")
matrixList = list()
matrixList[[rnas]] = list()
if (rnaSize > 0) {
rnaSize2 = rnaSize
} else{
rnaSize2 = maxPos
}
message(paste(" ***** RNA Size: ",
rnaSize2, " ***** "))
matrixList[[rnas]][["noHost"]] = list()
matrixList[[rnas]][["noHost"]] = getMatrices(InputFiles[[rnas]][["noHost"]],
rnas, rnaSize2)
names(matrixList[[rnas]][["noHost"]]) = sampleNames
matrixList[[rnas]][["original"]] = list()
matrixList[[rnas]][["original"]] = getMatrices(InputFiles[[rnas]][["original"]],
rnas, rnaSize2)
names(matrixList[[rnas]][["original"]]) = sampleNames
###########################################################
message(" ***** Creating object ***** ")
message(" *****-------*******************-------****** ")
message(" ******************************************** ")
message(" ******************************************** ")
#create rnaCrosslink dataset object
object = new(
"rnaCrosslinkDataSet",
rnas = rnas,
rnaSize = rnaSize2,
sampleTable = sampleTable,
InputFiles = InputFiles,
matrixList = matrixList,
clusterGrangesList = list(),
clusterTableList = list(),
clusterTableFolded = data.frame(),
interactionTable = data.frame(),
viennaStructures = list(),
dgs = list()
)
return(object)
}
JLP-BioInf/comradesOO documentation built on April 28, 2024, 4:22 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions rnaCrosslinkDataSet
Documented in rnaCrosslinkDataSet
#' @include rnaCrosslinkOO.R
#' rnaCrosslinkDataSet
#'
#' An S4 class to represent a rnaCrosslink dataset
#' @rdname rnaCrosslinkDataSet
#' @export
#'
setClass(
"rnaCrosslinkDataSet",
slots = c(
rnas = "character",
rnaSize = "numeric",
sampleTable = "data.frame",
# meta data
InputFiles = "list",
# data tables
matrixList = "list",
clusterGrangesList = "list",
clusterTableList = "list",
clusterTableFolded = "data.frame",
interactionTable = "data.frame",
viennaStructures = "list",
dgs = "list"
),
prototype = list()
)
setValidity("rnaCrosslinkDataSet", function(object) {
})
#' rnaCrosslinkDataSet
#'
#' \code{rnaCrosslinkDataSet} objects are used to store the input meta-data, data and
#' create a framework for the storage of results. Whilst creating the object,
#' the original Input files are also filtered for the RNA of interest. Check the
#' package vignette for more information.
#'
#'
#' @param rnas vector - The names of the RNA interest, these must be displayed
#' the same way as in the input Input Files.
#' @param rnaSize named list - The sizes (nt) of the RNAs of interest, the list
#' elements must have same names as the \code{rnas} vector and each each contain
#' one numeric value.
#' @param sampleTable string - The address of the sample table, the sample table
#' must have 4 columns, fileName (the full path and file name of the input
#' Input file for each sample ), group ("s" - sample or "c" - control),
#' sample (1,2,3, etc), sampleName (must be unique).
#' @param subset a vector of 4 values to subset based on structural read size. c(l-min,l-max,r-min,r-max)
#' @param sample The number of reads to sample for each sample.
#'
#' @return A rnaCrosslinkDataSet object.
#'
#'
#'
#' @slot clusterTableFolded table - a table similar to the \code{clusterTableList}
#' it contains coordinates of the clusters along with vienna format fold and
#' RNA sequences for each cluster
#' @slot clusterTableList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. contains a table
#' with coordinates and information about the clusters identified
#' @slot clusterGrangesList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. contains GRanges
#' objects of the original duplexes with their cluster membership
#' @slot sampleTable table - Column names; fileName, group (s or c),
#' sample (1,2,3, etc), sampleName (must be unique)
#' @slot rnas string - a single RNA to analyse - must be present in \code{rnas(cdsObject)}
#' @slot rnaSize if set to 0 this will be calculated
#' @slot matrixList List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{matrixList(cds)[[rna]][[type]][[sample]]}. Contains a set
#' of contact matrices, each cell contains the number of duplexes identified
#' for position x,y.
#' @slot InputFiles List - Follows the pattern for list slots of rnaCrosslinkDataSet
#' objects, \code{InputFiles(cds)[[rna]][[type]][[sample]]}. Contains a set of
#' tables, these are the original Input files that were read in.
#' @slot interactionTable Table of interactions discovered in step1 of the folding
#' @slot viennaStructures List of vienna format structures from final prediction
#' @slot dgs List of free energies
#'
#' @name rnaCrosslinkDataSet
#' @docType class
#' @rdname rnaCrosslinkDataSet
#'
#' @examples
#' # make example input
#' cds = makeExamplernaCrosslinkDataSet()
#'
#'cds
#'
#' @export
rnaCrosslinkDataSet <- function(rnas,
rnaSize = 0 ,
sampleTable,
subset = "all",
sample = "all") {
###########################################################
# Read in the sample table
###########################################################
# check the inputs here, stop if wrong
message(" ******************************************** ")
message(" ***** rnaCrosslink-OO ****** ")
message(" ******************************************** ")
message(" *****-------*******************-------****** ")
message(" ***** Reading SampleTable ****** ")
# Read in sample table
#check for more than two samples
# if( nrow(sampleTable) < 2 ){
# stop( "The sample Table must contain at least 1
# sample and 1 control" )
# }
message(paste(" ***** Detected ",
nrow(sampleTable), " Samples ****** "))
###########################################################
#check column names of sampleTable
colnamesST = c("file", "group", "sample", "sampleName")
if (all(colnames(sampleTable) != colnamesST)) {
stop("Column names of metaData table should be :
file, group, sample, sampleNames")
}
# Get the comparison groups check group has the c and s
if (!(unique(as.character(sampleTable$group))[1] %in% c("c", "s") &
unique(as.character(sampleTable$group))[2] %in% c("c", "s"))) {
stop("Groups should be c and s")
}
# Make group into a list with control and sample
group = sampleTable[, "group"]
group2 = list()
group2[["c"]] = which(group == "c")
group2[["s"]] = which(group == "s")
group = group2
message(paste(
" ***** detected group c::",
paste(group[["c"]],
collapse = " ") ,
paste(rep(" ",
2),
collapse = ""),
" ***** "
))
message(paste(
" ***** detected group s::",
paste(group[["s"]],
collapse = " ") ,
paste(rep(" ",
(
2)),
collapse = ""),
" ***** "
))
###########################################################
# Get the sampleNames
sampleNames = c()
if (is.null(sampleTable$sampleName)) {
stop("The sample Table must have a column named sampleName")
} else if (length(unique(sampleTable$sampleName)) !=
length(sampleTable$sampleName)) {
stop("Sample names must be unique")
} else{
sampleNames = as.character(sampleTable$sampleName)
spaces = (length(sampleNames) * (3 - length(sampleNames))) * 2
if(spaces < 0 ){spaces = 0}
message(paste(
" **** ",
paste(rep(" ",
spaces,
collapse = ""),
" Sample Names: ",
paste(sampleNames, collapse = " "),
paste(rep(" ",
spaces,
collapse = ""),
" **** "
))))
}
###########################################################
# Read in the Input files
###########################################################
#load the files into a list
message(" ***** Reading Input Files ***** ")
InputFiles = list()
InputFiles[["all"]] = list()
InputFiles[["all"]][["all"]] = list()
# read in the tables
inputs <- lapply(as.character(sampleTable$file),
function(file)
read.table(file,colClasses = c("character",
"character",
"character",
"character",
"integer",
"integer",
"integer",
"integer",
"character",
"character",
"integer",
"integer",
"integer",
"integer",
"character")))
#check column names
if (all(sapply(inputs, function(file)
! (identical(
colnames(file),
c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
))))) {
stop(
" The input files do not look they are produced with the
nextflow pipeline, please check the documentation. "
)
}
#subset based on user options
message(" ***** Checking Subsetting Options ***** ")
if(length(subset) > 1){
if( (subset[1] > subset[2]) | (subset[3] > subset[4]) ){
stop("Subsetting options do not look right, min value is geater than max")
}
}
if(length(subset) == 1){
message(" ***** No user subsetting chosen ***** ")
}else{
message(paste(" ***** Subsetting ","leftMinMax = ",subset[1],
subset[2],
"RightMinMax = ",subset[3],
subset[4]," ***** "))
inputs <- lapply(inputs, function(x){
x = x[which( (c(x$V6 - x$V5) > subset[1] & c(x$V6 - x$V5) < subset[2]) &
(c(x$V14 - x$V13) > subset[3] & c(x$V14 - x$V13) < subset[4]) ),]
colnames(x) = c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
x
})
}
message(" ***** Checking Sampling Options ***** ")
if(sample == "all"){
message(" ***** No user sampling chosen ***** ")
}else{
message(paste(" ***** Sampling ",sample,
"Structural duplexes ***** "))
inputs <- lapply(inputs, function(x){
x = x[sample(1:nrow(x),size = sample,replace = F),]
colnames(x) = c(
"V1",
"V2",
"V3",
"V4",
"V5",
"V6",
"V7",
"V8",
"V9",
"V10",
"V11",
"V12",
"V13",
"V14",
"V15"
)
x
})
}
checkRNA = function(inputs, rna) {
rnas %in% c(inputs$V4, inputs$V10)
}
rnaCheck = sapply(inputs, checkRNA, rna = rnas)
if(!any(rnaCheck)){
stop(
"No match for chosen RNA exists in this dataSet"
)
}
inputs = lapply(inputs, function(x) x[complete.cases(x),] )
inputs = lapply(inputs, function(x) x[!is.infinite(x$V8),] )
inputs = lapply(inputs, function(x) x[!is.infinite(x$V14),] )
InputFiles[["all"]][["all"]] = inputs
names(InputFiles[["all"]][["all"]]) = sampleNames
#get the maxpos
getMax = function(file, rna) {
return(max(file[file$V10 == rnas, "V14"],
max(file[file$V4 == rnas, "V8"])))
}
maxPos = max(sapply(inputs, getMax, rna = rnas))
###########################################################
message(" ***** Getting RNAs of Interest ****** ")
message(" ***** RNA of interest + Host RNA ***** ")
InputFiles[[rnas]][["original"]] = swapInputs(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
InputFiles[[rnas]][["host"]] = swapInputs3(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
message(" ***** RNA of interest Alone ***** ")
InputFiles[[rnas]][["noHost"]] = swapInputs2(InputList = InputFiles[["all"]][["all"]],
rna = rnas)
###########################################################
# Make matrices of the specific RNA without host
###########################################################
message(" ***** Making Matrices ****** ")
matrixList = list()
matrixList[[rnas]] = list()
if (rnaSize > 0) {
rnaSize2 = rnaSize
} else{
rnaSize2 = maxPos
}
message(paste(" ***** RNA Size: ",
rnaSize2, " ***** "))
matrixList[[rnas]][["noHost"]] = list()
matrixList[[rnas]][["noHost"]] = getMatrices(InputFiles[[rnas]][["noHost"]],
rnas, rnaSize2)
names(matrixList[[rnas]][["noHost"]]) = sampleNames
matrixList[[rnas]][["original"]] = list()
matrixList[[rnas]][["original"]] = getMatrices(InputFiles[[rnas]][["original"]],
rnas, rnaSize2)
names(matrixList[[rnas]][["original"]]) = sampleNames
###########################################################
message(" ***** Creating object ***** ")
message(" *****-------*******************-------****** ")
message(" ******************************************** ")
message(" ******************************************** ")
#create rnaCrosslink dataset object
object = new(
"rnaCrosslinkDataSet",
rnas = rnas,
rnaSize = rnaSize2,
sampleTable = sampleTable,
InputFiles = InputFiles,
matrixList = matrixList,
clusterGrangesList = list(),
clusterTableList = list(),
clusterTableFolded = data.frame(),
interactionTable = data.frame(),
viennaStructures = list(),
dgs = list()
)
return(object)
}
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