HolmBonferroni  R Documentation 
Apply the HolmBonferroni method to adjust for multiple hypothesis tests performed on quartets from a data set of gene trees.
HolmBonferroni(pTable, model, alpha = 0.05)
pTable 
a table of quartets with pvalues, as computed by

model 
one of 
alpha 
a critical value, for rejection of adjusted pvalues less than or equal to 
When pvalues are computed for each quartet using
quartetTreeTestInd
or quartetStarTestInd
,
multiple comparisons are being done for one dataset. The
HolmBonferroni method \insertCiteHolmBonf79MSCquartets adjusts these pvalues upward,
controlling the familywise error rate. The probability
of at least one false discovery (rejection of the null hypothesis)
is no more than the significance level.
The HolmBonferroni method does not require that test hypotheses are independent, which is important for its application to quartet counts presumed to have arisen on a single species tree.
This can be a low power test (often failing to reject when the null hypothesis is false). In particular for the T1 and T3 tests, it does not consider the relationships between edge lengths for different sets of four taxa.
the same table, with rows reordered, and 2 new columns of 1) adjusted pvalues, and 2) "Y" or "N" for indicating "reject" or "fail to reject"
HolmBonf79MSCquartets
quartetTreeTestInd
, quartetStarTestInd
gtrees=read.tree(file=system.file("extdata","dataGeneTreeSample",package="MSCquartets")) taxanames=taxonNames(gtrees) QT=quartetTable(gtrees,taxanames[1:6]) RQT=quartetTableResolved(QT) pTable=quartetTreeTestInd(RQT,"T3") pTable[1:10,] HBpTable=HolmBonferroni(pTable,"T3",.05) HBpTable[1:10,]
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