process_wide_format: Merging rows with identical values in a particular column in...

In iq: Protein Quantification in Mass Spectrometry-Based Proteomics

Merging rows with identical values in a particular column in a table

Description

Collapses rows with identical values in a particular column in a table. When the values in each row are proportional such as intensities of multiple fragments of a protein, the MaxLFQ algorithm is recommended.

Usage

process_wide_format(input_filename,
                    output_filename,
                    id_column,
                    quant_columns,
                    data_in_log_space = FALSE,
                    annotation_columns = NULL,
                    method = "maxLFQ")

Arguments

input_filename	Input filename of a tab-separated value text file.
output_filename	Output filename.
id_column	The column where unique values will be kept. Rows with identical values in this column are merged. Rows with empty values here are removed.
quant_columns	Columns containing numerical data to be merged.
data_in_log_space	A logical value. If FALSE, the numerical data will be log2-transformed.
annotation_columns	Columns in the input file apart from id_column and quant_columns that will be kept in the output.
method	Method for merging. Default value is "maxLFQ". Possible values are "maxLFQ", "maxLFQ_R", "median_polish", "top3", "top5", "meanInt", "maxInt", "sum", "least_na" and any function for collapsing a numerical matrix to a row vector.

Details

Method "maxLFQ_R" implements the MaxLFQ algorithm pure R. It is slower than "maxLFQ".

Method "maxInt" selects row with maximum intensity (top 1).

Method "sum" sum all intensities.

Method "least_na" selects row with the least number of missing values.

The value of method can be a function such as function(x) log2(colSums(2^x, na.rm = TRUE)) for summing all intensities in the original space.

Value

The result table is written to output_filename. A NULL value is returned.

Author(s)

Thang V. Pham

References

Pham TV, Tran CTM, Henneman AA, Pham LHC, Le DG, Can AH, Bui PHL, Piersma SR, Jimenez CR. Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics. Journal of Proteome Research 2026 Feb 6; 25(2):1198–1203.

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.

iq documentation built on Oct. 28, 2026, 1:07 a.m.