modular wrapper to identify transcript groups of poor fit to current cell segments in space
Usage
runTranscriptErrorDetection(
chosen_cells,
score_GeneMatrix,
transcript_df,
cellID_coln = "CellId",
transID_coln = "transcript_id",
transGene_coln = "target",
score_coln = "score",
spatLocs_colns = c("x", "y", "z"),
model_cutoff = 50,
score_cutoff = -2,
svm_args = list(kernel = "radial", scale = FALSE, gamma = 0.4),
groupTranscripts_method = c("dbscan", "delaunay"),
distance_cutoff = "auto",
config_spatNW_transcript = NULL,
seed_transError = NULL
)Arguments
- chosen_cells
the cell_ID of chosen cells
- score_GeneMatrix
the gene x cell-type matrix of log-like score of gene in each cell type
- transcript_df
the data.frame of transcript_ID, cell_ID, score, spatial coordinates
- cellID_coln
the column name of cell_ID in transcript_df
- transID_coln
the column name of transcript_ID in transcript_df
- transGene_coln
the column name of target or gene name in transcript_df
- score_coln
the column name of score in transcript_df
- spatLocs_colns
the column names of 1st, 2nd, optional 3rd spatial dimension of each transcript in transcript_df
- model_cutoff
the cutoff of transcript number to do spatial modeling (default = 50)
- score_cutoff
the cutoff of score to separate between high and low score transcripts (default = -2)
- svm_args
a list of arguments to pass to svm function, typically involve kernel, gamma, scale
- groupTranscripts_method
use either "dbscan" or "delaunay" method to group transcripts in space (default = "dbscan")
- distance_cutoff
maximum molecule-to-molecule distance within same transcript group (default = "auto")
- config_spatNW_transcript
configuration list to create spatial network at transcript level, see manual for
createSpatialDelaunayNW_from_spatLocsfor more details, set to NULL to use default config- seed_transError
seed for transcript error detection step, default = NULL to skip the seed