runOrderedClusteringGenome: Run hierarchical clustering preserving order

View source: R/local_correlations.R

runOrderedClusteringGenomeR Documentation

Run hierarchical clustering preserving order

Description

Run hierarchical clustering preserving sequential order of entries

Usage

runOrderedClusteringGenome(
  X,
  gr,
  method = c("adjclust", "hclustgeo"),
  quiet = FALSE,
  alpha = 0.5,
  adjacentCount = 500,
  setNANtoZero = FALSE,
  method.corr = c("pearson", "spearman")
)

Arguments

X

data matrix were *rows* are features in sequential order

gr

GenomicRanges object with entries corresponding to the *rows* of X

method

'adjclust': adjacency constrained clustering. 'hclustgeo': incorporate data correlation and distance in bp

quiet

suppress messages

alpha

use by 'hclustgeo': mixture parameter weighing correlations (alpha=0) versus chromosome distances (alpha=1)

adjacentCount

used by 'adjclust': number of adjacent entries to compute correlation against

setNANtoZero

replace NAN correlation values with a zero

method.corr

Specify type of correlation: "pearson", "kendall", "spearman"

Details

Use adjacency constrained clustering from adjclust package:

Alia Dehman, Christophe Ambroise and Pierre Neuvial. 2015. Performance of a blockwise approach in variable selection using linkage disequilibrium information. BMC Bioinformatics 16:148 doi.org:10.1186/s12859-015-0556-6

Or, use hclustgeo in ClustGeo package to generate hierarchical clustering that roughly preserves sequential order.

Chavent, et al. 2017. ClustGeo: an R package for hierarchical clustering with spatial constraints. arXiv:1707.03897v2 doi:10.1007/s00180-018-0791-1

Value

list hclust tree, one entry for each chromosome

Examples

library(GenomicRanges)
library(EnsDb.Hsapiens.v86)

# load data
data('decorateData')

# load gene locations
ensdb = EnsDb.Hsapiens.v86

# Evaluate hierarchical clustering
treeList = runOrderedClusteringGenome( simData, simLocation ) 

# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList )

# Plot correlations and clusters in region defined by query
query = range(simLocation)

plotDecorate( ensdb, treeList, treeListClusters, simLocation, query)


GabrielHoffman/decorate documentation built on May 23, 2023, 1:29 a.m.