metamorphr (version 0.2.0)

read_featuretable: Read a feature table into a tidy tibble

Description

Basically a wrapper around readr::read_delim() but performs some initial tidying operations such as gather() rearranging columns. The label_col will be renamed to Feature.

Usage

read_featuretable(file, delim = ",", label_col = 1, metadata_cols = NULL, ...)

Value

A tidy tibble.

Arguments

file

A path to a file but can also be a connection or literal data.

delim

The field separator or delimiter. For example "," in csv files.

label_col

The index or name of the column that will be used to label Features. For example an identifier (e.g., KEGG, CAS, HMDB) or a m/z-RT pair.

metadata_cols

The index/indices or name(s) of column(s) that hold additional feature metadata (e.g., retention times, additional identifiers or m/z values).

...

Additional arguments passed on to readr::read_delim()

References

• H. Wickham, J. Stat. Soft. 2014, 59, DOI 10.18637/jss.v059.i10.

• H. Wickham, M. Averick, J. Bryan, W. Chang, L. McGowan, R. François, G. Grolemund, A. Hayes, L. Henry, J. Hester, M. Kuhn, T. Pedersen, E. Miller, S. Bache, K. Müller, J. Ooms, D. Robinson, D. Seidel, V. Spinu, K. Takahashi, D. Vaughan, C. Wilke, K. Woo, H. Yutani, JOSS 2019, 4, 1686, DOI 10.21105/joss.01686.

• “12 Tidy data | R for Data Science,” can be found under https://r4ds.had.co.nz/tidy-data.html, 2023.

Examples

# Read a toy dataset in the format produced with Bruker MetaboScape (Version 2021).
featuretable_path <- system.file("extdata", "toy_metaboscape.csv", package = "metamorphr")

# Example 1: Provide indices for metadata_cols
featuretable <- read_featuretable(featuretable_path, metadata_cols = 2:5)

featuretable

# Example 2: Provide a name for label_col and indices for metadata_cols
featuretable <- read_featuretable(
  featuretable_path,
  label_col = "m/z",
  metadata_cols = c(1, 2, 4, 5)
)

featuretable

# Example 3: Provide names for both, label_col and metadata_cols
featuretable <- read_featuretable(
  featuretable_path,
  label_col = "m/z",
  metadata_cols = c("Bucket label", "RT", "Name", "Formula")
)

featuretable