read_compounddiscoverer: Read compound discoverer output

read_compounddiscovererR Documentation

Read compound discoverer output

Description

Read compound discoverer output

Usage

read_compounddiscoverer(
  dir = getwd(),
  files = list.files(path = dir, pattern = "(RP|HILIC).*\\.csv$", full.names = TRUE),
  colname_regex = "^(.*)\\d{8,8}_+(.*)_+((HILIC|RP)(NEG|POS))\\.raw.*$",
  colname_format = function(x) stringi::stri_replace_first_regex(x, colname_regex,
    "$1$2"),
  mod_extract = function(x) stringi::stri_subset_regex(x, colname_regex) %>%
    stringi::stri_replace_first_regex(colname_regex, "$3"),
  quantity = NULL,
  nonames = FALSE,
  exclude_sname_pattern = "(blank|QC|RS)",
  subgroups = NULL,
  logbase = 2,
  impute = FALSE,
  plot = FALSE,
  label = "feature_id",
  pca = plot,
  pls = plot,
  fit = if (plot) "limma" else NULL,
  formula = ~subgroup,
  block = NULL,
  coefs = NULL,
  contrasts = NULL,
  palette = NULL,
  verbose = TRUE
)

Arguments

dir

compound discoverer output directory

files

compound discoverer output files

colname_regex

regular expression to parse sample names from column names

colname_format

function to reformat column names

mod_extract

function to extract MS modi from sample names

quantity

'area', 'normalizedarea' or NULL

nonames

TRUE or FALSE: retain compunds without Names?

exclude_sname_pattern

regular expression of sample names to exclude

subgroups

NULL or string vector : subgroups to retain

logbase

base for logarithmization of the data

impute

TRUE or FALSE: impute group-specific NA values?

plot

TRUE or FALSE: plot ?

label

fvar

pca

TRUE or FALSE: run pca ?

pls

TRUE or FALSE: run pls ?

fit

model engine: 'limma', 'lm', 'lme(r)', 'wilcoxon' or NULL

formula

model formula

block

model blockvar: string or NULL

coefs

model coefficients of interest: character vector or NULL

contrasts

coefficient contrasts of interest: character vector or NULL

palette

color palette : named character vector

verbose

TRUE or FALSE : message ?

Value

SummarizedExperiment


bhagwataditya/importomics documentation built on Nov. 28, 2024, 8:28 a.m.