read_rectangles: Read omics data from rectangular file

In bhagwataditya/importomics: Unified statistal Modeling of Omics Data

Read omics data from rectangular file

Description

Read omics data from rectangular file

Usage

.read_rectangles(
  file,
  sheet = 1,
  fid_rows,
  fid_cols,
  sid_rows,
  sid_cols,
  expr_rows,
  expr_cols,
  fvar_rows = NULL,
  fvar_cols = NULL,
  svar_rows = NULL,
  svar_cols = NULL,
  fdata_rows = NULL,
  fdata_cols = NULL,
  sdata_rows = NULL,
  sdata_cols = NULL,
  transpose = FALSE,
  verbose = TRUE
)

read_rectangles(
  file,
  sheet = 1,
  fid_rows,
  fid_cols,
  sid_rows,
  sid_cols,
  expr_rows,
  expr_cols,
  fvar_rows = NULL,
  fvar_cols = NULL,
  svar_rows = NULL,
  svar_cols = NULL,
  fdata_rows = NULL,
  fdata_cols = NULL,
  sdata_rows = NULL,
  sdata_cols = NULL,
  transpose = FALSE,
  sfile = NULL,
  sfileby = NULL,
  subgroupvar = character(0),
  verbose = TRUE
)

Arguments

file	string: name of text (txt, csv, tsv, adat) or excel (xls, xlsx) file
sheet	integer/string: only relevant for excel files
fid_rows	numeric vector: featureid rows
fid_cols	numeric vector: featureid cols
sid_rows	numeric vector: sampleid rows
sid_cols	numeric vector: sampleid cols
expr_rows	numeric vector: expr rows
expr_cols	numeric vector: expr cols
fvar_rows	numeric vector: fvar rows
fvar_cols	numeric vector: fvar cols
svar_rows	numeric vector: svar rows
svar_cols	numeric vector: svar cols
fdata_rows	numeric vector: fdata rows
fdata_cols	numeric vector: fdata cols
sdata_rows	numeric vector: sdata rows
sdata_cols	numeric vector: sdata cols
transpose	TRUE or FALSE (default)
verbose	TRUE (default) or FALSE
sfile	sample file
sfileby	sample file mergeby column
subgroupvar	subgroupvar in sfile

Value

SummarizedExperiment

Examples

# RNASEQ
   file <- system.file('extdata/billing19.rnacounts.txt', package = 'autonomics')
   read_rectangles( file, fid_rows = 2:25,     fid_cols = 2,
                          sid_rows = 1,        sid_cols = 5:28,
                         expr_rows = 2:25 ,   expr_cols = 5:28,
                         fvar_rows = 1,       fvar_cols = 1:4,
                        fdata_rows = 2:25 ,  fdata_cols = 1:4,   transpose = FALSE)
# LCMSMS PROTEINGROUPS
   file <- system.file('extdata/billing19.proteingroups.txt', package = 'autonomics')
   read_rectangles(  file,
                     fid_rows = 2:21,    fid_cols = 383,
                     sid_rows = 1,       sid_cols = seq(124, 316, by = 6),
                    expr_rows = 2:21,   expr_cols = seq(124, 316, by = 6),
                    fvar_rows = 1,      fvar_cols = c(2, 6, 7, 383),
                   fdata_rows = 2:21,  fdata_cols = c(2, 6, 7, 383),
                   transpose  = FALSE )
# SOMASCAN
   file <- system.file('extdata/atkin.somascan.adat', package = 'autonomics')
   read_rectangles(file, fid_rows = 30,         fid_cols = 23:42,
                         sid_rows = 42:108,     sid_cols = 4,
                        expr_rows = 42:108,    expr_cols = 23:42,
                        fvar_rows = 28:40,     fvar_cols = 22,
                        svar_rows = 41,        svar_cols = 1:21,
                       fdata_rows = 28:40,    fdata_cols = 23:42,
                       sdata_rows = 42:108,   sdata_cols = 1:21,  transpose  = TRUE)
# METABOLON
   file <- system.file('extdata/atkin.metabolon.xlsx', package = 'autonomics')
   read_rectangles(file, sheet = 2,
                     fid_rows = 11:30,     fid_cols = 2,
                     sid_rows = 4,         sid_cols = 15:81,
                    expr_rows = 11:30,    expr_cols = 15:81,
                    fvar_rows = 10,       fvar_cols = 1:14,
                    svar_rows = 1:10,     svar_cols = 14,
                   fdata_rows = 11:30,   fdata_cols = 1:14,
                   sdata_rows = 1:10,    sdata_cols = 15:81,
                    transpose = FALSE )

bhagwataditya/importomics documentation built on May 1, 2024, 2:01 a.m.