Read Transcriptomics Data — rna.read

Reads transcriptomics data from one/several file(s) or dataframe and creates a SummarizedExperiment object.

Usage

rna.read_data(
  data = NULL,
  files.ind = NULL,
  expdesign = NULL,
  csvsep = ";",
  dec = ".",
  sheet = 1,
  name = "SymbolID",
  id = "gene_id",
  values = "FPKM",
  id2name.table = NULL,
  id2name.id = NULL,
  id2name.name = NULL,
  pfx.counts = "counts.",
  rsd_thresh = NULL,
  filt_type = c("condition", "complete", "fraction", NULL),
  filt_thr = 3,
  filt_min = NULL
)

Arguments

data: File or dataframe containing transcriptomics data, if files.ind is not used.
files.ind: Prefixes of several files in the working directory containing transcriptomics data, if data is not used.
expdesign: Experimental design as file path or data frame, if made previously.
csvsep: Delimiter if reading CSV file(s).
dec: Decimal separator if reading CSV, TSV, or TXT files.
sheet: Sheet of an Excel file to be read.
name: Header of column containing primary gene IDs (e.g., gene names).
id: Header of column containing alternative gene IDs (e.g., locus IDs).
values: Name of the column containing the values (if files.ind != NULL).
id2name.table: File containing a table with ID to name mappings.
id2name.id: Header of column containing alternative gene IDs in id2name.table.
id2name.name: Header of column containing primary gene IDs in id2name.table.
pfx.counts: Prefix in headers of columns containing gene abundances (if data != NULL).
rsd_thresh: Provide a relative standard deviation (RSD) threshold in % for genes. The RSD is calculated for each condition and if the maximum RSD value determined for a given protein exceeds rsd_thresh, the gene is discarded. The RSD filter is applied before further missing value filters based on the three filt_ arguments.
filt_type: (Character string) "complete", "condition" or "fraction", Sets the type of filtering applied. "complete" will only keep genes with valid values in all samples. "condition" will keep genes that have a maximum of filt_thr missing values in at least one condition. "fraction" will keep genes that have a filt_min fraction of valid values in all samples.
filt_thr: (Integer) Sets the threshold for the allowed number of missing values in at least one condition if filt_type = "condition". In other words: "keep genes that have a maximum of 'filt_thr' missing values in at least one condition."
filt_min: (Numeric) Sets the threshold for the minimum fraction of valid values allowed for any genes if filt_type = "fraction".

Value

Returns a SummarizedExperiment object.