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Restructure classes and their responsibilities

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Elias Projahn 2021-12-16 13:01:44 +01:00
parent 01ec301d6d
commit e2b93babe5
27 changed files with 974 additions and 634 deletions
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38
man/preset.Rd
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@ -5,24 +5,20 @@
\title{Create a new preset.}
\usage{
preset(
methods = c("clusteriness", "correlation", "neural", "adjacency", "proximity"),
species_ids = NULL,
gene_ids = NULL,
reference_gene_ids = NULL,
optimization_target = "mean_rank"
methods = all_methods(),
species_ids = geposan::species$id,
gene_ids = geposan::genes$id,
reference_gene_ids
)
}
\arguments{
\item{methods}{Methods to apply.}
\item{methods}{List of methods to apply.}
\item{species_ids}{IDs of species to include.}
\item{gene_ids}{IDs of genes to screen.}
\item{reference_gene_ids}{IDs of reference genes to compare to.}
\item{optimization_target}{Parameter of the reference genes that the ranking
should be optimized for.}
}
\value{
The preset to use with \code{\link[=analyze]{analyze()}}.
@ -33,25 +29,7 @@ analysis. Note that the genes to process should normally include the
reference genes to be able to assess the results later. The genes will be
filtered based on how many species have data for them. Genes which only have
orthologs for less than 25\% of the input species will be excluded from the
preset and the analyis.
}
\details{
Available methods are:
\itemize{
\item \code{clusteriness} How much the gene distances to the nearest telomere
cluster across species.
\item \code{correlation} The mean correlation of gene distances to the nearest
telomere across species.
\item \code{neural} Assessment by neural network trained on the reference genes.
\item \code{adjacency} Proximity to reference genes.
\item \code{proximity} Mean proximity to telomeres.
}
Available optimization targets are:
\itemize{
\item \code{mean} Mean rank of the reference genes.
\item \code{median} Median rank of the reference genes.
\item \code{max} First rank of the reference genes.
\item \code{min} Last rank of the reference genes.
}
preset and the analyis. See the different method functions for the available
methods: \code{\link[=clustering]{clustering()}}, \code{\link[=correlation]{correlation()}}, \code{\link[=neural]{neural()}}, \code{\link[=adjacency]{adjacency()}} and
\code{\link[=proximity]{proximity()}}.
}