preprocess_scores: Helper function to deal with tensor sparsity and liana's...

preprocess_scoresR Documentation

Helper function to deal with tensor sparsity and liana's scores as in Python

Description

Helper function to deal with tensor sparsity and liana's scores as in Python

Usage

preprocess_scores(
  context_df_dict,
  score_col = "magnitude_rank",
  sender_col = "source",
  receiver_col = "target",
  ligand_col = "ligand.complex",
  receptor_col = "receptor.complex",
  outer_fraction = 0,
  invert = TRUE,
  invert_fun = function(x) 1 - x,
  non_negative = TRUE,
  non_negative_fill = 0,
  lr_sep = "^",
  verbose = TRUE
)

Arguments

context_df_dict

Dictionary (named list) containing a dataframe for each context. The dataframe must contain columns containing sender (source) cells, receiver (target) cells, ligands, receptors, and communication scores, separately. Keys are context names and values are dataframes. NULL by default. If not NULL will be used instead of 'sce@metadata$liana_res'.

score_col

Name of the column containing the communication scores in all context dataframes.

sender_col

Name of the column containing the sender cells in all context dataframes.

receiver_col

Name of the column containing the receiver cells in all context dataframes.

ligand_col

Name of the column containing the ligands in all context dataframes.

receptor_col

Name of the column containing the receptors in all context dataframes.

outer_fraction

controls the elements to include in the union scenario of the 'how' options. Only elements that are present at least in this fraction of samples/contexts will be included. When this value is 0, considers all elements across the samples. When this value is 1, it acts as using ‘how=’inner''

invert

boolean wheter to invert the score (TRUE by defeault)

invert_fun

function used to invert scores

non_negative

whether to set negative scores to 0

non_negative_fill

the value to be used to fill negative values

lr_sep

ligand-receptor separator; '^' by default.

verbose

verbosity logical


saezlab/ligrec_decoupler documentation built on Aug. 10, 2024, 8:56 a.m.