Query the coefficients of the selected models

queryCoeff() returns the coefficients of a group of terms for the genes whose selected model (sc.t.fit()) passes rsq and p_value and has a non-zero coefficient for every term of the group. It also prints the formula of the model.

Usage

queryCoeff(
  scmpObj,
  rsq = 0.7,
  p_value = scmpObj@Parameters@p_value,
  query = "pseudotime_path",
  change = NULL,
  strictly = FALSE,
  verbose = TRUE
)

Arguments

scmpObj: A ScMaSigPro object.
rsq: The smallest R-squared of the selected model of a gene.
p_value: The largest p-value of the selected model of a gene; by default that of sc.p.vector().
query: The terms: "pseudotime", the powers of pseudotime of the reference path; "pseudotime_path" or "path_pseudotime", their products with the path dummies; "path", the path dummies.
change: NULL, or "increasing" or "decreasing": keep the genes whose coefficients of the query add up to a positive (negative) number, or with strictly = TRUE are all positive (negative).
strictly: See change.
verbose: Whether to print progress messages.

Value

A data frame of coefficients: one row per gene that passes the thresholds and the query, one column per queried term.

Author

Priyansh Srivastava spriyansh29@gmail.com.

Examples

data("scmp.ob", package = "scMaSigPro")
# Genes whose coefficients of pseudotime are all positive
queryCoeff(scmp.ob,
    query = "pseudotime", change = "increasing", strictly = TRUE,
    verbose = FALSE
)
#> Polynomial-GLM Formula: beta0 + beta1*Path2vsPath1 + beta2*scmp_binned_pseudotime + beta3*scmp_binned_pseudotimexPath2
#>        betascmp_binned_pseudotime
#> Gene9                  0.08220353
#> Gene18                 0.08788562
#> Gene25                 0.04003636
#> Gene40                 0.03289285
#> Gene46                 0.12313411
#> Gene52                 0.04574704
#> Gene62                 0.02188666
#> Gene81                 0.02422643
#> Gene83                 0.01054990
#> Gene86                 0.12192126
#> Gene89                 0.07235517