Pre_process_input: Pre-processing of RNAseq data

In Jorisvansteenbrugge/TcT: Trait-based Comparative Transcriptomics

Pre-processing of RNAseq data

Description

Wrapper of preprocess functions, including: Identifying Matrix features, Normalization, Filtering for non informative lines

Usage

Pre_process_input(
  file.path,
  database,
  normalize.method = T,
  filter.method = "MAD",
  filter.low.coverage = T,
  filter.genes.zero = F,
  normalization.features = NULL,
  taxon_file = NULL
)

Arguments

normalize.method	User defined method to normalize data
filter.low.coverage	boolean expression to wether we should filter out
filter.genes.zero	False or a number. The number indicates the number of zeros that can max be present. Genes with more zeros than the cut-off get pruned. genomes with a low overall expression level.
filepath	RNAseq data file

Value

RNAseq.data A list object containin the RNAseq table with ranked expression collumns possible filtered and normalized, together with some features (position of expression collumns, rank collumns, annotation database, a list of the genomes, and a presence absence table of all annotations)

Author(s)

JJM van Steenbrugge

Examples

Pre_process_input(file.path, normalize.method = FALSE, filter.method = FALSE) #No normalization or filtering
Pre_process_input(file.path, normalize.method = TRUE, filter.method = 'MAD') # Default Normalization, and MAD filtering
Pre_process_input(file.path, normalize.method = custom_function_name, filter.method = FALSE) # Custom Normalization, no filtering

Jorisvansteenbrugge/TcT documentation built on Sept. 26, 2022, 6:50 a.m.