fast_preprocess: Data filtering and normalization

In iq: Protein Quantification in Mass Spectrometry-Based Proteomics

Data filtering and normalization

Description

Filters out low intensities and performs median normalization.

Usage

fast_preprocess(quant_table,
                median_normalization = TRUE,
                log2_intensity_cutoff = 0,
                pdf_out = "qc-plots-fast.pdf",
                pdf_width = 12,
                pdf_height = 8,
                show_boxplot = TRUE)

Arguments

quant_table	The quant_table component as returned by fast_read.
median_normalization	A logical value. The default TRUE value is to perform median normalization.
log2_intensity_cutoff	Entries lower than this value in log2 space are ignored. Plot a histogram of all intensities to set this parameter.
pdf_out	A character string specifying the name of the PDF output. A NULL value will suppress the PDF output.
pdf_width	Width of the pdf output in inches.
pdf_height	Height of the pdf output in inches.
show_boxplot	A logical value. The default TRUE value is to create boxplots of fragment intensities for each sample.

Value

A list is returned with the same components as input data in which low intensities are filtered out and median normalization is performed if requested.

Author(s)

Thang V. Pham

References

Pham TV, Henneman AA, Jimenez CR. iq: an R package to estimate relative protein abundances from ion quantification in DIA-MS-based proteomics. Bioinformatics 2020 Apr 15;36(8):2611-2613.

See Also

fast_read

iq documentation built on March 31, 2023, 11:34 p.m.