wrapper_regionAssignment: The wrapper function to assign region information to sample...
In maplesword/RefSimSpec:

Description Usage Arguments Value

View source: R/RSS.r

This function assign the brain region information to the given sample (cell) clusters, based on their transcriptome similarities to the ABA reference data sets. Progenitors and neurons are processed separately.

wrapper_regionAssignment(input, clust, progenitorClustIdx,
  neuronClustIdx = setdiff(sort(unique(clust)), progenitorClustIdx),
  geneSetNeurons = "regionGroup_fetalA10",
  geneSetProgenitors = "regionGroup_fetalB10",
  strucGroups = c("structure_group", "structure_acronym"),
  thresBinA10 = NULL, thresBinB10 = NULL, threads = 1,
  verbose = TRUE, previous = NULL)

`input`	The input matrix of sample (cell) transcriptome profiles. Should be properly normalized and log-transformed. Its rows representing genes should be named by ENSEMBL IDs, gene symbols or Entrez IDs.
`clust`	Cluster indices of samples (cells)
`progenitorClustIdx`	Names of the progenitor clusters
`neuronClustIdx`	Names of the neuron clusters (by default, it is the complementary cluster set of progenitorClustIdx)
`geneSetNeurons`	The predefined gene set for calculation of ABA-RSS of neurons
`geneSetProgenitors`	The predefined gene set for calculation of ABA-RSS of progenitors
`thresBinA10`	The correlation thresholds for different brain regions to determine highly correlated neuron samples (cells). Five predefined threshold lists are available (X0.75, X0.8, X0.85, X0.9 and X0.95). When it is NULL, X0.85 is used. The users can also customized the threshold by assigning a numeric vector with the same length of the number of brain regions (19).
`thresBinB10`	Similar to thresBinA10 but for the progenitor samples (cells).
`threads`	The number of threads to run.
`verbose`	Whether to output the progress information.
`previous`	Previous output. When it is given, the RSS will not be re-calculated.
`strucGroup`	The structure labels to use: 'structure_acronym' for the directly measured structures; 'structure_group' for the grouped structures.