cluster_estimates: Cluster both estimated transitions

In taiawu/dsfworld_package: Visualizes and Analyzes Differential Scanning Fluorimetry Data

Cluster both estimated transitions

Description

Groups estimated transtions, without distinguishing between major and minor, using hclust. Sorts estimations into clusters, and overwrites the input est_row with the cluster number to which the estimate was assigned. Individual clusters are defined by a minimum inter-cluster distance. With default usage, clusters the estimates using the row/measurement number of the estimates (corresponding to temperature), with minimum inter-measurment distance of 4.

Usage

cluster_estimates(est_df, .est_row_col = "est_row", min_dist = 4, ...)

Arguments

est_df	a tibble of estimated transitions, as output by tidy_estimates
.est_row_col	a string, providing the name of the numeric column passed to hclust. Defaults to "est_row", the measurment number of the estimated transtion.
min_dist	the minimum distance between two estimates. Defaults to 4. For a dataset with one measurement per degree, this corresponds to a minimum inter-estimate distance of 4 degrees.
...	permit the presence additional parameters, which may be passed via ... from upstream functions, but are ignored here.

Details

I don't recall how carefully I considered the downstream consequences of over-writing the given row. If the clustering fails, is all of this informaiton lost? It might be good to specify a safer behavior in the hclust_points function.

Value

the input tibble, with identical format, but the input .est_row_col overwritten by the cluster number to which the estimate belongs.

See Also

hclust_points

taiawu/dsfworld_package documentation built on June 18, 2024, 5:39 a.m.