Takes the output of a minc modelling function and computes False Discovery Rate thresholds.
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mincFDR(buffer, ...) ## S3 method for class 'mincSingleDim' mincFDR(buffer, df, mask = NULL, method = "qvalue", ...) ## S3 method for class 'mincLogLikRatio' mincFDR(buffer, mask = NULL, ...) ## S3 method for class 'mincLmer' mincFDR(buffer, mask = NULL, method = "fdr", ...) ## S3 method for class 'mincMultiDim' mincFDR(buffer, columns = NULL, mask = NULL, df = NULL, method = "FDR", statType = NULL, ...)
The results of a mincLm type run.
extra parameters to pass to methods
The degrees of freedom - normally this can be determined from the input object.
Either a filename or a numeric vector representing a mask only values inside the mask will be used to compute the threshold.
The method used to compute the false discovery rate. Options are "FDR" and "pFDR".
A vector of column names. By default the threshold will be computed for all columns; with this argument the computation can be limited to a subset.
This should be either a "t","F","u","chisq" or "tlmer" depending upon the type of statistic being thresholded.
This function uses the
qvalue package to compute the
False Discovery Rate threshold for the results of a mincLm
computation. The False Discovery Rate represents the percentage of
results expected to be a false positive. Two implementations can be
used as specified by the method argument. "FDR" uses the
p.adjust, whereas "pFDR" is a version of the
postivie False Discovery Rate as found in John Storey's
package. The main interface functions are
mincFDR.mincMultiDim The workhorse function, used to compute q-values and thresholds for sets of minc volumes
mincFDR.logLikRatio Similar to above, but calculates thresholds by parametric bootstrap when possible
mincFDR.mincSingleDim Used when mincLm-like results are written out and read back in
either to the same or another R session. In this case it loses it's
and must be converted back
vertexFDR Used with results of a vertexLm-like command. Results are converted internally to resemble a mincMultiDim and processed as normal
A object of type
mincQvals with the same number of columns
as the input (or the subset specified by the columns argument to
mincFDR). Each column now contains the qvalues for each voxel. Areas
outside the mask (if a mask was specified) will be represented by a
value of 1. The result also has an attribute called "thresholds"
which contains the 1, 5, 10, 15, and 20 percent false discovery rate
mincWriteVolume,mincLm,mincWilcoxon or mincTtest
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## Not run: getRMINCTestData() # read the text file describing the dataset gf <- read.csv("/tmp/rminctestdata/test_data_set.csv") # run a linear model relating the data in all voxels to Genotype vs <- mincLm(jacobians_fixed_2 ~ Sex, gf) # compute the False Discovery Rate qvals <- mincFDR(vs) ## End(Not run)
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