score_predictors: Scoring Predictors with a Selected Set of Criteria
In chenyenchung/genofeatutil: Utilities for genomic feature manipulation

Description Usage Arguments Details Value Examples

score_predictors() scores the predictor-target pair according to the percentage of increment of MSE, the dominance of the predictive power ( represented by a gap in MSE among the predictors), correlation of expression levels, and whether position-weighted matrix-inferred motif score of the predictor is high near the target.

score_predictors(x, gap.ratio = 0.3, mse.threshold = 0.1,
  cor.threshold = 0.3, weight = c(1, 1, 1, 1, 1, 1, 1),
  expMat = NULL, expMat.type = "csv", use.row = TRUE,
  motif.list = NULL, score.path = NULL, motif.path = NULL,
  top.motif.number = NULL, motif.threshold = NULL, db = NULL)

`x`	a data frame containing the predictors, targets, and percentage increment of MSE (or other measures of predictor power)
`gap.ratio`	a number indicating the threshold of "having a gap in MSE"; any %IncMSE beyond gap.ratio * the whole range of %IncMSE will be seen as a gap and get +1 in score
`mse.threshold`	a number indicating the threshold of individual %IncMSE; any %IncMSE beyond this threshold gets +1 in score
`cor.threshold`	a number indicating the threshold of individual correlation of expression of the predictor-target pair; any correlation beyond this thresold gets +1 in score
`weight`	a numeric vector indicating the weights to sum up different scores; the length is 7 with a default of c(1, 1, 1, 1, 1, 1, 1, 1). The order of seven scores is "Raw%IncMSE", "gap", "MSE_threshold", "cor_threshold", "Pearson_cor", "motif_score_sum", "motif_score_presence".
`expMat`	a data frame containing an expression matrix or a character string containing a path to a csv / rds / rdata file containing an expression matrix
`expMat.type`	a character string indicating the expMat file type if `expMat` is a path
`use.row`	a logical value indicating whether the gene names are in the row names or column names of the expression matrix loaded
`motif.list`	a list generated by `get_motif_info()`; if this argument is not NULL, it has higher priority than `score.path` and `motif.path`
`score.path`	a character string indicating the path to a SCENIC motif score dataset
`motif.path`	a character string indicating the path to a SCENIC motif list
`top.motif.number`	a numeric value indicating the number of top motifs in terms of score to keep; the default is NULL and keeping all
`motif.threshold`	a numeric value indicting the threshold score for motifs; only motifs with scores higher than this value will be kept; the default value is NULL and keeping all
`db`	a list generated by `make_database()`

To score the predictors, this function takes motif database from SCENIC (motif analysis), an expression matrix (correlation analysis), and a gene name conversion database from make_database().

a data frame containing the scores of each target-predictor pair

# Loading dummydb
dummypath <- system.file("extdata", "dummy.gtf", package = "genofeatutil")
testdb <- make_database(species = "test", gtf.path = dummypath)

# Generate dummy result for demo
dummyresult <- data.frame("predictor" = c("tf_1", "tf_2", "tf_3"),
                          "target" = rep("alias1.2", 3),
                          "Raw_%IncMSE" = c(0.3, 0.1, 1e-3),
                          row.names = NULL, stringsAsFactors = FALSE)

dummyexpMat <- data.frame("sample1" = c(3, 1, 1, 3),
                          "sample2" = c(1, 1, 3, 2),
                          "sample3" = c(1, 3, 1, 1),
                          row.names = c("tf_1", "tf_2", "tf_3", "alias1.2"),
                          stringsAsFactors = FALSE)
# Example score data frame
score_result <- score_predictors(x = dummyresult,
                                 expMat = dummyexpMat,
                                 use.row = TRUE,
                                 score.path = system.file(
                                   "extdata",
                                   "scoremat.feather",
                                   package = "genofeatutil"),
                                 motif.path = system.file(
                                   "extdata",
                                   "dummy_motif.tbl",
                                   package = "genofeatutil"),
                                 db = testdb)