repClonalFamily | R Documentation |
This function uses the PHYLIP package to make phylogenetic analysis. For making trees it uses maximum parsimony methods.
repClonalFamily(.data, .vis_groups, .threads, .nofail)
.data |
The data to be processed, output of repAlignLineage() function. |
.vis_groups |
Groups for visualization, used to annotate specific clones on chart and display them in different colors. This is a named list, where names are for the chart legend, and list items are clone IDs that belong to the groups. It's not necessary to assign groups to all clonotypes; unassigned ones will be displayed on the chart as "Clonotype" category. It's also possible to assign multiple clonotypes to the same group by providing nested lists or vectors of clone IDs instead of single clone IDs. Example: .vis_groups = list(A = 817, B = 201, C = list(303, 42)) |
.threads |
Number of threads to use. |
.nofail |
Returns NA instead of stopping if PHYLIP is not installed. Used to avoid raising errors in examples on computers where PHYLIP is not installed. |
Dataframe or list of dataframes (if input is a list with multiple samples). The dataframe has these columns: * Cluster: cluster name * Germline.Input: germline sequence, like it was in the input; not aligned * Germline.Output: germline sequence, parsed from PHYLIP dnapars function output; it contains difference of germline from the common ancestor; "." characters mean matching letters * Common.Ancestor: common ancestor sequence, parsed from PHYLIP dnapars function output * Trunk.Length: mean trunk length, representing the distance between the most recent common ancestor and germline sequence as a measure of the maturity of a lineage * Tree: output tree in "phylo" format, loaded from by PHYLIP dnapars function output * TreeStats: nested dataframe containing data about tree nodes, needed for visualization * Sequences: nested dataframe containing all sequences for this combination of cluster and germline; it contains regions from original sequences, saved for repSomaticHypermutation() calculation, and also data needed for visualizations
data(bcrdata)
bcr_data <- bcrdata$data
bcr_data %>%
seqCluster(seqDist(bcr_data), .fixed_threshold = 3) %>%
repGermline(.threads = 1) %>%
repAlignLineage(.min_lineage_sequences = 2, .align_threads = 2, .nofail = TRUE) %>%
repClonalFamily(.threads = 1, .nofail = TRUE)
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