EpivizMetagenomicsData-class {metavizr} | R Documentation

## Data container for MRexperiment objects

### Description

Used to serve metagenomic data (used in e.g., icicle plots and heatmaps). Wraps `MRexperiment-class` objects.

### Methods

`df_to_tree(root, df)`

  Helper function to recursively build nested response for getHierarchy

  root

    Root of subtree

  df

    data.frame containing children to process

`getAlphaDiversity(measurements = NULL)`

  Compute alpha diversity using vegan for the given samples

  measurements

    Samples to compute alpha diversity

  start

    Start of feature range to query

  end

    End of feature range to query

`getCombined(measurements = NULL, seqName, start = 1, end = 1000, order = NULL, nodeSelection = NULL, selectedLevels = NULL)`

  Return the counts aggregated to selected nodes for the given samples

  measurements

    Samples to get counts for

  seqName

    name of datasource

  start

    Start of feature range to query

  end

    End of feature range to query

  order

    Ordering of nodes

  nodeSelection

    Node-id and selectionType pairs

  selectedLevels

    Current aggregation level

`get_default_chart_type()`

  Get name of default chart type for this data type

`getHierarchy(nodeId = NULL)`

  Retrieve feature hierarchy information for subtree with specified root

  nodeId

    Feature identifier with level info

`get_measurements()`

  Get description of measurements served by this object

`getPCA(measurements = NULL)`

  Compute PCA over all features for given samples

  measurements

    Samples to compute PCA over

  start

    Start of feature range to query

  end

    End of feature range to query

`getRows(measurements = NULL, start = 1, end = 1000, selectedLevels = 3, selections = NULL)`

  Return the sample annotation and features within the specified range and level for a given sample and features

  measurements

    Samples to retrieve for

  start

    Start of feature range to query

  end

    End of feature range to query

  selections

    Node-id and selectionType pairs

  selectedLevels

    Current aggregation level

`getValues(measurements = NULL, start = 1, end = 1000, selectedLevels = 3, selections = NULL, row_order = NULL)`

  Return the counts for a sample within the specified range

  measurements

    Samples to get counts for

  start

    Start of feature range to query

  end

    End of feature range to query

  selections

    Node-id and selectionType pairs

  selectedLevels

    Current aggregation level

`propagateHierarchyChanges(selection = NULL, order = NULL, selectedLevels = NULL, request_with_labels = FALSE)`

  Update internal state for hierarchy

  selection

    Node-id and selectionType pairs

  order

    Ordering of features

  selectedLevels

    Current aggregation level

  request_with_labels

    For handling requests using fData entries from MRexperiment

`row_to_dict(row)`

  Helper function to format each node entry for getHierarchy response

  row

    Information for current node.

`searchTaxonomy(query = NULL, max_results = 15)`

  Return list of features matching a text-based query

  query

    String of feature for which to search

  max_results

    Maximum results to return

`toNEO4JDbHTTP(batch_url, neo4juser, neo4jpass, datasource, description = NULL)`

  Write an 'EpivizMetagenomicsData' object to a Neo4j graph database

  @param batch_url (character) Neo4j database url and port for processing batch http requests @param neo4juser (character) Neo4j database user name @param neo4jpass (character) Neo4j database password @param datasource (character) Name of Neo4j datasource node for this 'EpivizMetagenomicsData' object

  @examples library(metagenomeSeq) data("mouseData") mobj <- metavizr:::EpivizMetagenomicsData$new(object=mouseData) mobj$toNEO4JDbHTTP(batch_url = "http://localhost:7474/db/data/batch", neo4juser = "neo4juser", neo4jpass = "neo4jpass", datasource = "mouse_data")

`update(new_object, send_request = TRUE)`

  Update underlying data object with new object

### Examples

    library(metagenomeSeq)
    data(mouseData)
    obj <- metavizr:::EpivizMetagenomicsData$new(mouseData, feature_order = colnames(fData(mouseData)))

[Package metavizr version 1.2.1 Index]