fast_MaxLFQ: The MaxLFQ algorithm

In iq: Protein Quantification in Mass Spectrometry-Based Proteomics

The MaxLFQ algorithm

Description

A fast implementation of the MaxLFQ algorithm.

Usage

fast_MaxLFQ(norm_data, row_names = NULL, col_names = NULL)

Arguments

norm_data	A list of four vectors with equal length protein_list, sample_list, id and quant as prepared by the fast_preprocess function or the quant_table component returned by the fast_read function. Note that quant should contain log2 intensities.
row_names	A vector of character strings for row names. If NULL, unique values in the protein_list component of norm_data will be used. Otherwise, it should be the first column of the protein component returned by the fast_read.
col_names	A vector of character strings for column names. If NULL, unique values in the sample_list component of norm_data will be used. Otherwise, it should be the sample component returned by the fast_read.

Value

A list is returned with two components

estimate	A quantification result table in log2 space.
annotation	A vector of strings indicating membership in case of multiple connected components for each row of estimate.

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, fast_preprocess

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