mainAnalysis {RNAither} | R Documentation |
Performs a standard analysis of the data (quality and statistics) from a dataset file.
mainAnalysis(header, dataset, flagForSameExp, listOfNormalizations, listOfArgs4norm, listOfStatTests, listOfArgs4stat, multTestAdj, hitScoringVec1, hitScoringVec2, posNegFlag, flag4Gsea, vecOfChannels, whichOnto)
header |
the header of a dataset file generated with generateDatasetFile |
dataset |
an R data frame generated with generateDatasetFile |
flagForSameExp |
either 0 or 1. If 1, all experiments defined in the column ScreenNb in the dataset file must have the same design (same type and same number of replicates - exact plate layout is irrelevant) so that Spearman's correlation coefficient can be computed between experiments (each with summarized replicates) |
listOfNormalizations |
a list of the normalization function to apply. Can be LiWongRank , varAdjust , divNorm , quantileNormalization , BScore , ZScore , ZScorePerScreen , subtractBackground , lowessNorm , controlNorm |
listOfArgs4norm |
a list containing, for each element of listofnormalizations , the arguments to be passed on |
listOfStatTests |
a list of the statistical tests to perform. Can be Ttest , MannWhitney , RankProduct |
listOfArgs4stat |
a list containing, for each element of listofstattests , the arguments to be passed on |
multTestAdj |
indicates the p-value correction for multiple testing - one of "holm" , "hochberg" , "hommel" , "bonferroni" , "BH" , "BY" , "fdr" , or "none" (Type ?p.adjust for details)) |
hitScoringVec1 |
a vector of length 3 indicating (in that order):
- scoring according to p-value (0: no, 1: yes) - scoring according to ZScore with ZScore < threshold (0: no, 1: yes), or according to ZScore < threshold and p-value < hitScoringVec2[1] (2) - scoring according to ZScore with ZScore > threshold (0: no, 1: yes), or according to ZScore > threshold and p-value < hitScoringVec2[1] (2). If hitScoringVec1[2] or hitScoringVec1[3] are equal to 2, hitScoringVec1[1] must be equal to one, otherwise p-values will not be computed. |
hitScoringVec2 |
a vector of length 3 indicating the thresholds for hitscoringvec1 |
posNegFlag |
either 0 (no controls available) or 1 (controls available) |
flag4Gsea |
Can be:
- either 0: No GSEA analysis is performed - or 1: A GSEA analysis is performed for each hit scoring method - or a binary vector that allows to choose which hit scoring method(s) will be used for a GSEA analysis. Hit scoring methods are sorted as follows: first, hits are scored according to the p-values of each test specified in listOfStatTests . Then, if the option of scoring hits according to p-values and Intensities is chosen (see hitScoringVec1 , for each test, a hit vector is generated. Finally, if the option of scoring hits according to Intensities only is chosen, hit vectors are generated for this option.
|
vecOfChannels |
a character vector containing the names of the channels to be used for quality plots, for example "SigIntensity" or "NbCells" |
whichOnto |
one of the three GO hierarchies: "biological_process" , "molecular_function" or "cellular_component" - used for the GSEA analysis |
Generates the html output files index.html
and indexnorm.html
containing the quality analysis of raw and normalized data, respectively, and stats.html
, containing the statistical analysis. If several normalization methods are applied, an indexnorm
file is generated after each.
data(exampleHeader, package="RNAither") data(exampleDataset, package="RNAither") mainAnalysis(header, dataset, 0, list(controlNorm), list(list(1, 0, "SigIntensity", 1)), list(Ttest, MannWhitney), list(list("l", 1, "SigIntensity", "GeneName"), list("l", 1, "SigIntensity", "GeneName")), "none", c(1, 0, 0), c(0.05, 0, 0), 1, 1, c("SigIntensity", "NbCells"), "biological_process")