Description Usage Arguments Value Examples
View source: R/identify-regions.R
Identifies regions of interest (the tips of branches, or branching regions) based on comparing the GAP scores#'acquired by running local clustering by 'kbranches.local'. Performs local filtering to reduce noise in the extracted labels.
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input_dat: |
data frame of input data with rows=samles and cols=dimensions. |
mode: |
=c('tip','branch') find either the tips or the branching regions |
tip_mode: |
=c('2','3','both') find the tips using the GAP statistic of 1 vs 2,3 or both |
gap_scores: |
list, output of function 'kbranches.local' for the same 'input_dat' |
smoothing_region: |
number of neighbours in to consider for label filtering |
smoothing_region_thresh: |
minimum number of thresholds with same label in the neighbourhood required for the sample to keep it's label |
Dist: |
matrix of sample to sample distances |
dotsize1: |
size of points of class1 (red), used when plotting in 3D |
dotsize2: |
size of points of class2 (green), used when plotting in 3D |
nclust: |
number of clusters (tips/branching regions). If left NULL, will be estimated. |
nclust.max: |
maximum possible number of clusters to consider. Only used if nclust==NULL |
B.max: |
maximum number of bootstrap datasets used to calculate the GAP statistic to estimate nclust. Only used if nclust==NULL |
SE.factor: |
used to estimate nclust, argument to cluster::maxSE. Only used if nclust==NULL |
repeats: |
number of times to estimate nclust (for stability - the nclust most frequently considered 'best' is finally extracted). Only used if nclust==NULL |
a list with elements:
- is_in_region: a logical vector indicating which samples are part of the region (TRUE) and which not (FALSE)
- is_in_region_filtered: same as 'is_in_region', but after S_neib filtering to reduce noise.
- cluster: cluster assignment for each of the data points in is_in_region_filtered
- nclust: number of clusters identified, or specified by the user
- cluster_frequency: how many times (out of 'repeats') each number of clusters (of the nclust.max) was considered 'best'. NULL if nclust was provided by the user
1 | #see example of kbranches.local
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