Construct a kNN cell-cell interaction network and identify gene topics

Construct a kNN cell-cell interaction network and identify gene topics

rcpp_mmutil_network_topic_data(
  mtx_file,
  row_file,
  col_file,
  latent_factor,
  knn,
  output,
  write_sample_network = FALSE,
  output_sample_incidence = NULL,
  output_sample_adjacency = NULL,
  r_batches = NULL,
  CUTOFF = 1e-04,
  WEIGHTED = TRUE,
  MAXW = 1,
  KNN_BILINK = 10L,
  KNN_NNLIST = 10L,
  NUM_THREADS = 1L,
  MAX_ROW_WORD = 2L,
  ROW_WORD_SEP = "_",
  MAX_COL_WORD = 100L,
  COL_WORD_SEP = "@"
)

Arguments

mtx_file

data file (feature x n)

row_file

row file (feature x 1)

col_file

row file (n x 1)

latent_factor

(n x K)

knn

kNN parameter

output

file header for resulting files

write_sample_network

Do we want sample inc/adj? (default: FALSE)

output_sample_incidence

file header for sample adj (default: NULL)

r_batches

batch names (n x 1, default: NULL)

CUTOFF

expression present/absent call cutoff (default: 0)

WEIGHTED

include edge weights in feature calculation (default: TRUE)

MAXW

maximum edge weight (default: 1)

KNN_BILINK

num. of bidirectional links (default: 10)

KNN_NNLIST

num. of nearest neighbor lists (default: 10)

NUM_THREADS

number of threads for multi-core processing

MAX_ROW_WORD

maximum words per line in row_file

ROW_WORD_SEP

word separation character to replace white space

MAX_COL_WORD

maximum words per line in col_file

COL_WORD_SEP

word separation character to replace white space

Value

feature.incidence, sample.incidence, sample.adjacency