scale_abundance-methods: Scale the counts of transcripts/genes

In tidybulk: Brings transcriptomics to the tidyverse

Description

scale_abundance() takes as input a 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> | 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,
  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,
  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,
  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,
  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,
  action = "add",
  reference_selection_function = NULL
)

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

Arguments

.data	A 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> |
.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.
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

\lifecycle

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::counts_mini %>% 
   tidybulk(sample, transcript, count) %>% 
   identify_abundant() %>% 
   scale_abundance()

tidybulk documentation built on April 7, 2021, 6 p.m.