Allow customizing method metadata

man/adjacency.Rd

@@ -4,9 +4,21 @@
 \alias{adjacency}
 \title{Score genes based on their proximity to the reference genes.}
 \usage{
-adjacency(distance_estimate = densest, summarize = stats::median)
+adjacency(
+  id = "adjacency",
+  name = "Adjacency",
+  description = "Adjacency to reference genes",
+  distance_estimate = densest,
+  summarize = stats::median
+)
 }
 \arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
+
 \item{distance_estimate}{A function that will be used to summarize the
 distance values for each gene. See \code{\link[=densest]{densest()}} for the default
 implementation.}

man/clustering.Rd

@@ -4,7 +4,18 @@
 \alias{clustering}
 \title{Process genes clustering their distance to telomeres.}
 \usage{
-clustering()
+clustering(
+  id = "clustering",
+  name = "Clustering",
+  description = "Clustering of genes"
+)
+}
+\arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
 }
 \value{
 An object of class \code{geposan_method}.

man/correlation.Rd

@@ -4,9 +4,20 @@
 \alias{correlation}
 \title{Score genes based on their correlation with the reference genes.}
 \usage{
-correlation(summarize = stats::median)
+correlation(
+  id = "correlation",
+  name = "Correlation",
+  description = "Correlation with reference genes",
+  summarize = stats::median
+)
 }
 \arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
+
 \item{summarize}{A function for combining the different correlation
 coefficients into one metric. By default, \code{\link[stats:median]{stats::median()}} is used. Other
 suggested options include \code{\link[=max]{max()}} and \code{\link[=mean]{mean()}}.}

man/neural.Rd

@@ -4,9 +4,22 @@
 \alias{neural}
 \title{Find genes by training and applying a neural network.}
 \usage{
-neural(seed = 180199, n_models = 5, control_ratio = 0.5)
+neural(
+  id = "neural",
+  name = "Neural",
+  description = "Assessment by neural network",
+  seed = 180199,
+  n_models = 5,
+  control_ratio = 0.5
+)
 }
 \arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
+
 \item{seed}{The seed will be used to make the results reproducible.}
 
 \item{n_models}{This number specifies how many sets of training data should

man/proximity.Rd

@@ -4,9 +4,20 @@
 \alias{proximity}
 \title{Score the distance of genes to the telomeres across species.}
 \usage{
-proximity(summarize = stats::median)
+proximity(
+  id = "proximity",
+  name = "Proximity",
+  description = "Proximity to telomeres",
+  summarize = stats::median
+)
 }
 \arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
+
 \item{summarize}{A function for combining the different proximities into one
 metric. By default, \code{\link[stats:median]{stats::median()}} is used. Other suggested options
 include \code{\link[=min]{min()}} and \code{\link[=mean]{mean()}}.}

man/species_adjacency.Rd

@@ -4,9 +4,21 @@
 \alias{species_adjacency}
 \title{Score genes based on their adjacency to the reference genes within species.}
 \usage{
-species_adjacency(distance_estimate = stats::median, summarize = stats::median)
+species_adjacency(
+  id = "species_adjacency",
+  name = "Species adj.",
+  description = "Species adjacency",
+  distance_estimate = stats::median,
+  summarize = stats::median
+)
 }
 \arguments{
+\item{id}{Unique ID for the method and its results.}
+
+\item{name}{Human readable name for the method.}
+
+\item{description}{Method description.}
+
 \item{distance_estimate}{Function for combining the distance differences
 within one species.}