Title: | MiChip Parsing and Summarizing Functions |
---|---|
Description: | This package takes the MiChip miRNA microarray .grp scanner output files and parses these out, providing summary and plotting functions to analyse MiChip hybridizations. A set of hybridizations is packaged into an ExpressionSet allowing it to be used by other BioConductor packages. |
Authors: | Jonathon Blake <[email protected]> |
Maintainer: | Jonathon Blake <[email protected]> |
License: | GPL (>= 2) |
Version: | 1.61.0 |
Built: | 2024-12-07 05:54:56 UTC |
Source: | https://github.com/bioc/MiChip |
Creates a boxplot of expression data contained in a matrix and writes this to a file.
boxplotData(dmat, exptname, dlevel)
boxplotData(dmat, exptname, dlevel)
dmat |
matrix containing expression data to be boxplotted |
exptname |
Name of the experiment, used to build filename |
dlevel |
Stage of the experiment e.g. raw, summarized, normalized |
#Create a file of a boxplot containing normalized expression data for myexpt ## Not run: boxplotData(dmat, "MyExpt", "mednormed") ## End(Not run)
#Create a file of a boxplot containing normalized expression data for myexpt ## Not run: boxplotData(dmat, "MyExpt", "mednormed") ## End(Not run)
Creates a boxplot of expression data contained in a matrix.
boxplotDataNoFile(dmat, exptname, dlevel)
boxplotDataNoFile(dmat, exptname, dlevel)
dmat |
matrix containing expression data to be boxplotted |
exptname |
Name of the experiment, used to build plot title |
dlevel |
Stage of the experiment e.g. raw, summarized, normalized |
#Create a boxplot containing normalized expression data for myexpt ## Not run: boxplotDataNoFile(dmat, "MyExpt", "mednormed")
#Create a boxplot containing normalized expression data for myexpt ## Not run: boxplotDataNoFile(dmat, "MyExpt", "mednormed")
Spots flagged with a -ve quality flag value by the scanner may be regarded as not present. This method sets their intensity to NA.
correctForFlags(eset, intensityCutoff=0)
correctForFlags(eset, intensityCutoff=0)
eset |
|
intensityCutoff |
value of lowest acceptable intensity value in the experiment |
#Correct ExpressionSet for flags of spots marked as unreadable ## Not run: myCorrectedEset <-correctForFlags(eset, intensityCutoff=0) ## End(Not run)
#Correct ExpressionSet for flags of spots marked as unreadable ## Not run: myCorrectedEset <-correctForFlags(eset, intensityCutoff=0) ## End(Not run)
Alibrary for processing MiChip hybridizations
Jonathon Blake
Creates a median to summarize the intensities for individual probes, giving that not all probes will have a valid intensity reading
myForgivingMedian(mat, minSumlength=0)
myForgivingMedian(mat, minSumlength=0)
mat |
matrix of data to calculate the median from |
minSumlength |
The lowest acceptable length of the matrix to calculate a median |
#Calculate the median of a matrix omiting NAs ## Not run: myForgivingMedian(mat, minSumlength=0) ## End(Not run)
#Calculate the median of a matrix omiting NAs ## Not run: myForgivingMedian(mat, minSumlength=0) ## End(Not run)
Calculates the median of an array excluding NAs
naOmitMedian(mat, madAdjust=FALSE)
naOmitMedian(mat, madAdjust=FALSE)
mat |
A single dimensional matrix |
madAdjust |
if |
#Calculate the median of matrix mat omiting NAs ## Not run: myMedian <-naOmitMedian(mat, madAdjust=TRUE) ## End(Not run)
#Calculate the median of matrix mat omiting NAs ## Not run: myMedian <-naOmitMedian(mat, madAdjust=TRUE) ## End(Not run)
Normalizes intensity values to the median of each chip
normalizePerChipMedian(eset)
normalizePerChipMedian(eset)
eset |
|
#Normalize expression data in an Eset to the median ## Not run: normedDataEset <- normalizePerChipMedian(eset) ## End(Not run)
#Normalize expression data in an Eset to the median ## Not run: normedDataEset <- normalizePerChipMedian(eset) ## End(Not run)
Takes an ExpressionSet
and outputs a tab delimited file containing
feature annotation to the left and hyb specific expression/flag data to the right
outputAnnotatedDataMatrix(eset, exptname, stage, dataElement)
outputAnnotatedDataMatrix(eset, exptname, stage, dataElement)
eset |
|
exptname |
a string containing the name of the experiment. Used to build file name |
stage |
a string containing the stage of the data in the matrix e.g. normalized |
dataElement |
a string containing the name of the data element in the ExpressionSet to be output |
#Write out an annotated tab delimited file for the normalized data ## Not run: outputAnnotatedDataMatrix(normedEset, "MyMicroArrayExpt","Median_Normalized", "exprs") ## End(Not run)
#Write out an annotated tab delimited file for the normalized data ## Not run: outputAnnotatedDataMatrix(normedEset, "MyMicroArrayExpt","Median_Normalized", "exprs") ## End(Not run)
Adds a pearson correlation value to the scatter plots
panelCor(x,y, digits=2, prefix="r=")
panelCor(x,y, digits=2, prefix="r=")
x |
matrix of x values |
y |
matrix of y values to correlate with x |
digits |
number of digits to display |
prefix |
The string prefix that should be display on the scatterplot panel |
#Calculate the median of a matrix omiting NAs ## Not run: panelCor(x,y, digits=2, prefix="r=") ## End(Not run)
#Calculate the median of a matrix omiting NAs ## Not run: panelCor(x,y, digits=2, prefix="r=") ## End(Not run)
Loads all the gpr scanner output files in a particular directory and returns an
ExpressionSet
of the hybridizations in a MiChip experiment
parseRawData(datadir=".", pat="gpr")
parseRawData(datadir=".", pat="gpr")
datadir |
a directory containing one or my files of scanner output from MiChip hybridizations |
pat |
a string containing the three letter extension of the scanner output files |
## Not run: ## Load all *.gpr files in current directory parseRawData(datadir=".", pat="gpr") ## Load all *.gpr files in a specified directory , windows parseRawData(datadir="c:\mydata\grpdata\expt1\", pat="gpr") ## Load all *.gpr files in a specified directory, linux parseRawData(datadir="/home/myuser/gprdata/extp1/", pat="gpr") ## End(Not run)
## Not run: ## Load all *.gpr files in current directory parseRawData(datadir=".", pat="gpr") ## Load all *.gpr files in a specified directory , windows parseRawData(datadir="c:\mydata\grpdata\expt1\", pat="gpr") ## Load all *.gpr files in a specified directory, linux parseRawData(datadir="/home/myuser/gprdata/extp1/", pat="gpr") ## End(Not run)
Creates a pairwise set of scatter plots from a data matrix and writes it out to file
plotIntensitiesScatter(dmat, controls=NULL, exptname, maintitle)
plotIntensitiesScatter(dmat, controls=NULL, exptname, maintitle)
dmat |
matrix containing data from an experiment to be plotted |
controls |
matrix of row numbers containing control data to be plotted in a different colour |
exptname |
Name of the experiment, used for build the filename |
maintitle |
String used to build the maintitle of the graph |
#Plot the pairwise intensities from myexpt ## Not run: plotIntensitiesScatter(dmat, NULL, "MyExpt", "Median_Normalized") ## End(Not run)
#Plot the pairwise intensities from myexpt ## Not run: plotIntensitiesScatter(dmat, NULL, "MyExpt", "Median_Normalized") ## End(Not run)
Due to the requirements of spotting the chips, some of the spots are empty. Others contain controls or features from another species that may not be wanted in the analysis. This method removes them
removeUnwantedRows(rawData, filters)
removeUnwantedRows(rawData, filters)
rawData |
|
filters |
list of strings to be to be filtered from annotation gene name column |
#Removes empty and control spots from data matrix ## Not run: filters=c("empty", "control") filteredData <- removeUnwantedRows(rawData, filters) ## End(Not run)
#Removes empty and control spots from data matrix ## Not run: filters=c("empty", "control") filteredData <- removeUnwantedRows(rawData, filters) ## End(Not run)
Takes an ExpressionSet
and returns a data martix of
feature annotation to the left and hyb specific expression/flag data to the right
returnAnnotatedDataMatrix(eset, dataElement)
returnAnnotatedDataMatrix(eset, dataElement)
eset |
|
dataElement |
a string containing the name of the data element in the ExpressionSet to be output |
#Write out an annotated tab delimited file for the normalized data ## Not run: returnAnnotatedDataMatrix(normedEset,"exprs") ## End(Not run)
#Write out an annotated tab delimited file for the normalized data ## Not run: returnAnnotatedDataMatrix(normedEset,"exprs") ## End(Not run)
Any value less than the cutoff value will be set to NA. This allows near background intensity values to be excluded
setIntensityCutoff(dmat, intensityCutoff)
setIntensityCutoff(dmat, intensityCutoff)
dmat |
matrix of intensity values to which the cutoff value is applied |
intensityCutoff |
value of lowest acceptable intensity value in the experiment |
#Set all the values under 50 in a matrix to NA ## Not run: dmatOver50 <- setIntensityCutoff(dmat, 50) ## End(Not run)
#Set all the values under 50 in a matrix to NA ## Not run: dmatOver50 <- setIntensityCutoff(dmat, 50) ## End(Not run)
Removes all empty spots, control spots, U6 RNA, non human spots from an
ExpressionSet
in the standard fashion. A wrapper for removeUnwantedRows
standardRemoveRows(rawData)
standardRemoveRows(rawData)
rawData |
|
#Filter standard rows from an ExpressionSet ## Not run: myfilterdEset <-standardRemoveRows(rawData) ## End(Not run)
#Filter standard rows from an ExpressionSet ## Not run: myfilterdEset <-standardRemoveRows(rawData) ## End(Not run)
As the probes are spotted onto the in quaduplet or duplicate the values have to be combined in some way. This function takes the median of the intensities for the spots. Effectively the mean for duplicates. If less than half of the spots are present an NA is added
summarizeIntensitiesAsMedian(eset,minSumlength=0, madAdjust=FALSE)
summarizeIntensitiesAsMedian(eset,minSumlength=0, madAdjust=FALSE)
eset |
ExpressionSet containing probe intensity data to be summarized |
minSumlength |
The lowest acceptable length of the matrix to calculate a median |
madAdjust |
if |
#Calculate the median of a matrix omiting NAs ## Not run: summarizeIntensitiesAsMedian(eset,minSumlength=0,madAdjust=TRUE) ## End(Not run)
#Calculate the median of a matrix omiting NAs ## Not run: summarizeIntensitiesAsMedian(eset,minSumlength=0,madAdjust=TRUE) ## End(Not run)
Loads a set of hybridizations into a matrix and them proceeds to filter, summarize and median normalize them
workedExampleMedianNormalize(exptname, intensityCutoff=0, datadir=".", minSumlength, madAdjust = FALSE)
workedExampleMedianNormalize(exptname, intensityCutoff=0, datadir=".", minSumlength, madAdjust = FALSE)
exptname |
string indicating the name of the experiment |
intensityCutoff |
The intensity value for accepting the spots intensity value in the experiment |
datadir |
The directory where hybridization files are found. |
minSumlength |
Minimum exceptable number of values to summarize intensity value. |
madAdjust |
if |
#Normalize data in the current directory to the median per chip datadir <- system.file("extdata", package="MiChip") myNormedEset <-workedExampleMedianNormalize("MyExpt", intensityCutoff=0, datadir, minSumlength=0, madAdjust=TRUE)
#Normalize data in the current directory to the median per chip datadir <- system.file("extdata", package="MiChip") myNormedEset <-workedExampleMedianNormalize("MyExpt", intensityCutoff=0, datadir, minSumlength=0, madAdjust=TRUE)
Loads a set of hybridizations into a matrix and them proceeds to filter and summarize these data
workedExampleNotNormalizedData(exptname, intensityCutoff=0, datadir=".", minSumlength, madAdjust = FALSE )
workedExampleNotNormalizedData(exptname, intensityCutoff=0, datadir=".", minSumlength, madAdjust = FALSE )
exptname |
string indicating the name of the experiment |
intensityCutoff |
The intensity value for accepting the spots intensity value in the experment |
datadir |
The directory contain data from the experiment |
minSumlength |
Minimum exceptable number of values to summarize intensity value. |
madAdjust |
if |
#Summarizes the data in the current directory ## Not run: mySummarizedEset <-workedExampleNotNormalizedData("MyExpt", intensityCutoff=0, datadir=".", minSumlength=0, madAdjust=TRUE) ## End(Not run)
#Summarizes the data in the current directory ## Not run: mySummarizedEset <-workedExampleNotNormalizedData("MyExpt", intensityCutoff=0, datadir=".", minSumlength=0, madAdjust=TRUE) ## End(Not run)