View source: R/linkage_blocks_network.R
linkage_blocks_network | R Documentation |
This function identifies linkage blocks among markers using pairwise correlation between genotypes. The algorithm clusters adjacent, correlated markers using the fastgreedy community detection algorithm from R/igraph
linkage_blocks_network(
data_obj,
geno_obj,
collapse_linked_markers = TRUE,
threshold_power = 1,
plot_blocks = TRUE
)
data_obj |
a |
geno_obj |
a genotype object |
collapse_linked_markers |
A logical value. If TRUE markers are combined into linkage blocks based on correlation. If FALSE, each marker is treated as an independent observation. |
threshold_power |
A soft threshold power. The marker correlation matrix is raised to this power to increase or decrease the number of linkage blocks detected. Increasing the power makes more linkage blocks, and decreasing the power makes fewer linkage blocks. The default power is 1, which uses the correlation matrix as is. |
plot_blocks |
logical. If TRUE, the marker correlation matrices are plotted and the boundaries of the blocks are shown. |
Csardi G, Nepusz T: The igraph software package for complex network research, InterJournal, Complex Systems 1695. 2006. https://igraph.org
The correlation network can be optionally soft thresholded to increase or decrease resolution.
The data object is returned with a new list called linkage_blocks_collapsed if collapse_linked_markers is TRUE and linkage_blocks_full if collapse_linked_markers is FALSE Each element of the list is one linkage block and contains a vector naming the markers in that block. Blocks are named with a chromosome number and an index.
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