scale_abundance-methods: Scale the counts of transcripts/genes

In stemangiola/ttBulk: Brings transcriptomics to the tidyverse

Scale the counts of transcripts/genes

Description

scale_abundance() takes as input A 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment)) and Scales transcript abundance compansating for sequencing depth (e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25).

Usage

scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = "add",
  reference_selection_function = NULL
)

## S4 method for signature 'spec_tbl_df'
scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = "add",
  reference_selection_function = NULL
)

## S4 method for signature 'tbl_df'
scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = "add",
  reference_selection_function = NULL
)

## S4 method for signature 'tidybulk'
scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = "add",
  reference_selection_function = NULL
)

## S4 method for signature 'SummarizedExperiment'
scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = NULL,
  reference_selection_function = NULL
)

## S4 method for signature 'RangedSummarizedExperiment'
scale_abundance(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  method = "TMM",
  reference_sample = NULL,
  .subset_for_scaling = NULL,
  action = NULL,
  reference_selection_function = NULL
)

Arguments

.data	A 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment))
.sample	The name of the sample column
.transcript	The name of the transcript/gene column
.abundance	The name of the transcript/gene abundance column
method	A character string. The scaling method passed to the back-end function (i.e., edgeR::calcNormFactors; "TMM","TMMwsp","RLE","upperquartile")
reference_sample	A character string. The name of the reference sample. If NULL the sample with highest total read count will be selected as reference.
.subset_for_scaling	A gene-wise quosure condition. This will be used to filter rows (features/genes) of the dataset. For example
action	A character string between "add" (default) and "only". "add" joins the new information to the input tbl (default), "only" return a non-redundant tbl with the just new information.
reference_selection_function	DEPRECATED. please use reference_sample.

Details

'r lifecycle::badge("maturing")'

Scales transcript abundance compensating for sequencing depth (e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25). Lowly transcribed transcripts/genes (defined with minimum_counts and minimum_proportion parameters) are filtered out from the scaling procedure. The scaling inference is then applied back to all unfiltered data.

Underlying method edgeR::calcNormFactors(.data, method = c("TMM","TMMwsp","RLE","upperquartile"))

Value

A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'

A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'

A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'

A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'

A 'SummarizedExperiment' object

A 'SummarizedExperiment' object

Examples

 tidybulk::se_mini |>
   identify_abundant() |>
   scale_abundance()

stemangiola/ttBulk documentation built on April 10, 2024, 3:36 p.m.