combineScores.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/combineScores.R
\name{combineScores}
\alias{combineScores}
\alias{combineScoresPar}
\title{Combining values}
\usage{
combineScores(
  scores,
  method = c("max", "avg", "rcmax", "rcmax.avg", "BMA", "reciprocal"),
  round = FALSE,
  t = 0
)

combineScoresPar(scores, method, subSets = NULL, BPPARAM = NULL, ...)
}
\arguments{
\item{scores}{Matrix of scores to be combined}

\item{method}{one of \code{c("avg", "max", "rcmax", "rcmax.avg", "BMA", "reciprocal")}, see Details.}

\item{round}{Should the resulting value be rounded to the third digit?}

\item{t}{Numeric value to filter scores below this value. Only used in the
reciprocal method.}

\item{subSets}{List of combinations as info in other functions.}

\item{BPPARAM}{BiocParallel back-end parameters.
By default (\code{NULL}) a \code{for} loop is used.}

\item{...}{Other arguments passed to \code{combineScores}}
}
\value{
A numeric value as described in details.
}
\description{
Combine several similarities into one using several methods.
}
\details{
The input matrix can be a base matrix or a matrix from package Matrix.
The methods return:
\itemize{
\item \strong{avg}: The average or mean value.
\item \strong{max}: The max value.
\item \strong{rcmax}: The max of the column means or row means.
\item \strong{rcmax.avg}: The sum of the max values by rows and columns divided by
the number of columns and rows.
\item \strong{BMA}: The same as \code{rcmax.avg}.
\item \strong{reciprocal}: The double of the sum of the reciprocal maximal
similarities (above  a threshold) divided by the number of elements.
See equation 3 of the Tao \emph{et al} 2007 article.
}
}
\note{
\code{combineScores} is a version of the function of the same name in
package GOSemSim (\code{\link[GOSemSim:combineScores]{GOSemSim::combineScores()}}) with optional
rounding and some internal differences.
}
\examples{
(d <- structure(c(
    0.4, 0.6, 0.222222222222222, 0.4, 0.4, 0, 0.25, 0.5,
    0.285714285714286
),
.Dim = c(3L, 3L),
.Dimnames = list(c("a", "b", "c"), c("d", "e", "f"))
))
e <- d
sapply(c("avg", "max", "rcmax", "rcmax.avg", "BMA", "reciprocal"),
    combineScores,
    scores = d
)
d[1, 2] <- NA
sapply(c("avg", "max", "rcmax", "rcmax.avg", "BMA", "reciprocal"),
    combineScores,
    scores = d
)
colnames(e) <- rownames(e)
combineScoresPar(e, list(a = c("a", "b"), b = c("b", "c")),
    method = "max"
)
}
\references{
Ying Tao, Lee Sam, Jianrong Li, Carol Friedman, Yves A. Lussier;
Information theory applied to the sparse gene ontology annotation network to
predict novel gene function. Bioinformatics 2007; 23 (13): i529-i538.
doi: 10.1093/bioinformatics/btm195
}
\seealso{
\link[BiocParallel:register]{register} in BiocParallel about the arguments
accepted by BPPARAM.
}
\author{
Lluís Revilla based on Guangchuang Yu.
}