cluster_features: Cluster correlated features

In antonvsdata/notame: Workflow for non-targeted LC-MS metabolic profiling

Cluster correlated features

Description

Clusters features potentially originating from the same compound. Features with high Pearson correlation coefficient and small retention time difference are linked together. Then clusters are formed by setting a threshold for the relative degree that each node in a cluster needs to fulfil. Each cluster is named after the feature with the highest median peak area (median abundance) This is a wrapper around numerous functions that are based on the MATLAB code by David Broadhurst.

Usage

cluster_features(
  object,
  mz_col = NULL,
  rt_col = NULL,
  all_features = FALSE,
  rt_window = 1/60,
  corr_thresh = 0.9,
  d_thresh = 0.8,
  plotting = FALSE,
  min_size_plotting = 3,
  prefix = NULL
)

Arguments

object	a MetaboSet object
mz_col	the column name in fData(object) that holds mass-to-charge ratios
rt_col	the column name in fData(object) that holds retention times
all_features	logical, should all features be included in the clustering? If FALSE as the default, flagged features are not included in clustering
rt_window	the retention time window for potential links NOTE: use the same unit as the retention time
corr_thresh	the correlation threshold required for potential links between features
d_thresh	the threshold for the relative degree required by each node
plotting	should plots be drawn for each cluster?
min_size_plotting	the minimum number of features a cluster needs to have to be plotted
prefix	the prefix to the files to be plotted

Value

a MetaboSet object, with median peak area (MPA), the cluster ID, the features in the cluster, and cluster size added to fData.

See Also

find_connections, find_clusters, visualize_clusters, assign_cluster_id, compress_clusters

Examples

# The parameters are really weird because example data is imaginary
clustered <- cluster_features(example_set, rt_window = 1, corr_thresh = 0.5, d_thresh = 0.6)

antonvsdata/notame documentation built on Sept. 14, 2024, 11:09 p.m.