keep_variable-methods: Keep variable transcripts

In stemangiola/tidybulk: Brings transcriptomics to the tidyverse

Keep variable transcripts

Description

keep_variable() 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 returns a consistent object (to the input) with additional columns for the statistics from the hypothesis test.

Usage

keep_variable(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  top = 500,
  transform = log1p,
  log_transform = TRUE
)

## S4 method for signature 'spec_tbl_df'
keep_variable(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  top = 500,
  transform = log1p,
  log_transform = NULL
)

## S4 method for signature 'tbl_df'
keep_variable(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  top = 500,
  transform = log1p,
  log_transform = NULL
)

## S4 method for signature 'tidybulk'
keep_variable(
  .data,
  .sample = NULL,
  .transcript = NULL,
  .abundance = NULL,
  top = 500,
  transform = log1p,
  log_transform = NULL
)

## S4 method for signature 'SummarizedExperiment'
keep_variable(.data, top = 500, transform = log1p)

## S4 method for signature 'RangedSummarizedExperiment'
keep_variable(.data, top = 500, transform = log1p)

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
top	Integer. Number of top transcript to consider
transform	A function that will tranform the counts, by default it is log1p for RNA sequencing data, but for avoinding tranformation you can use identity
log_transform	DEPRECATED - A boolean, whether the value should be log-transformed (e.g., TRUE for RNA sequencing data)

Details

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

At the moment this function uses edgeR https://doi.org/10.1093/bioinformatics/btp616

Value

A consistent object (to the input) with additional columns for the statistics from the hypothesis test (e.g., log fold change, p-value and false discovery rate).

Underlying method: s <- rowMeans((x - rowMeans(x)) ^ 2) o <- order(s, decreasing = TRUE) x <- x[o[1L:top], , drop = FALSE] variable_trancripts = rownames(x)

A consistent object (to the input) with additional columns for the statistics from the hypothesis test (e.g., log fold change, p-value and false discovery rate).

A consistent object (to the input) with additional columns for the statistics from the hypothesis test (e.g., log fold change, p-value and false discovery rate).

A consistent object (to the input) with additional columns for the statistics from the hypothesis test (e.g., log fold change, p-value and false discovery rate).

A 'SummarizedExperiment' object

A 'SummarizedExperiment' object

Examples

	keep_variable(tidybulk::se_mini, top = 500)

stemangiola/tidybulk documentation built on Dec. 17, 2024, 11:12 p.m.