normalize: Normalize Seahorse data

In ceas: Cellular Energetics Analysis Software

Normalize Seahorse data

Description

Normalizes input data according to a sample normalization measure (e.g. cell number or \mug of protein). It assumes your data is background normalized.

Usage

normalize(
  seahorse_rates,
  norm_csv,
  norm_column = "well",
  norm_method = "minimum"
)

Arguments

seahorse_rates	The seahorse rates table read by the read_data() function.
norm_csv	A csv file with either well or experimental group in column 1 and the sample normalization measure in column 2. Headers are ignored.
norm_column	Whether to normalize by "well" or "exp_group" group. The first column of the normalization csv provided should match this value.
norm_method	How to normalize each well or experimental group (specified by norm_column): by its corresponding row in the norm_csv ("self") or by the minimum of the measure column in the provided norm_csv ("minimum"). See details.

Details

This normalization is distinct from the background normalization done by the Wave software. If the data are not background normalized, read_data() will output a warning showing rows with OCR, ECAR and PER values greater than 0.

Normalization Methods

When norm_method is set to "self", each OCR, ECAR, and PER value is divided by the measure it"self". OCR and ECAR values are divided by the corresponding raw value in the "measure" column: an intra-well or experimental group normalization. Each normalized value is then interpreted as pmol/min per measure (e.g. pmol/min/cell or pmol/min/\mug of protein.

When set to "minimum", each OCR, ECAR, and PER value is normalized by the minimum value in the norm_csv "measure" column. In this method, every "measure" column's value in the provided CSV file is divided by the lowest of the "measure" values to get a normalization factor for each well or experimental group. The OCR, ECAR, and PER values in each well or experimental group are divided by their corresponding normalization factors. Compared to "self", this is an inter-well/experimental group normalization based on the lowest "measure". The results may be interpreted as pmol/min per minimum of the measure (eg: group cell count or \mug of protein.)

Value

a normalized seahorse_rates data.table

Examples

rep_list <- system.file("extdata", package = "ceas") |>
  list.files(pattern = "*.xlsx", full.names = TRUE)
norm_csv <- system.file("extdata", package = "ceas") |>
  list.files(pattern = "^norm.csv", full.names = TRUE)
read.csv(norm_csv)
seahorse_rates <- read_data(rep_list, sheet = 2)
head(seahorse_rates, n = 10)
# normalize by experimental group based on the minimum cell count or protein quantity
seahorse_rates.normalized <- normalize(
  seahorse_rates,
  norm_csv,
  norm_column = "exp_group",
  norm_method = "minimum"
)
head(seahorse_rates.normalized, n = 10)

ceas documentation built on April 3, 2025, 8:34 p.m.