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57 lines
1.8 KiB
R
57 lines
1.8 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/preset.R
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\name{preset}
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\alias{preset}
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\title{Create a new preset.}
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\usage{
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preset(
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methods = c("clusteriness", "correlation", "neural", "adjacency", "proximity"),
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species_ids = NULL,
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gene_ids = NULL,
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reference_gene_ids = NULL,
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optimization_target = "mean_rank"
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)
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}
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\arguments{
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\item{methods}{Methods to apply.}
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\item{species_ids}{IDs of species to include.}
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\item{gene_ids}{IDs of genes to screen.}
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\item{reference_gene_ids}{IDs of reference genes to compare to.}
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\item{optimization_target}{Parameter of the reference genes that the ranking
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should be optimized for.}
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}
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\value{
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The preset to use with \code{\link[=analyze]{analyze()}}.
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}
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\description{
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A preset is used to specify which methods and inputs should be used for an
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analysis. Note that the genes to process should normally include the
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reference genes to be able to assess the results later. The genes will be
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filtered based on how many species have data for them. Genes which only have
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orthologs for less than 25\% of the input species will be excluded from the
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preset and the analyis.
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}
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\details{
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Available methods are:
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\itemize{
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\item \code{clusteriness} How much the gene distances to the nearest telomere
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cluster across species.
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\item \code{correlation} The mean correlation of gene distances to the nearest
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telomere across species.
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\item \code{neural} Assessment by neural network trained on the reference genes.
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\item \code{adjacency} Proximity to reference genes.
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\item \code{proximity} Mean proximity to telomeres.
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}
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Available optimization targets are:
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\itemize{
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\item \code{mean} Mean rank of the reference genes.
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\item \code{median} Median rank of the reference genes.
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\item \code{max} First rank of the reference genes.
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\item \code{min} Last rank of the reference genes.
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}
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}
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