Description

We assessed the performance of aLFQ and the different quantification estimation methods it supports by investigating a commercially available synthetic sample. The Universal Proteomic Standard 2 (UPS2) consists of 48 proteins spanning a dynamic range of five orders of magnitude in bins of eight proteins. The sample was measured in a complex background consisting of Mycobacterium bovis BCG total cell lysate in shotgun and targeted MS modes. Three datasets are available: UPS2_SC (spectral counts), UPS2_LFQ (MS1 intensity), UPS2_SRM (MS2 intensity).

Usage

Format

The data structure for UPS2_SRM represents a data.frame containing the following column header: "run_id" (freetext), "protein_id" (freetext), "peptide_id" (freetext), "transition_id" (freetext), "peptide_sequence" (unmodified, natural amino acid sequence in 1-letter nomenclature), "precursor_charge" (positive integer value), "transition_intensity" (positive non-logarithm floating value) and "concentration" (calibration: positive non-logarithm floating value, prediction: "?").

The data structure for UPS2_LFQ (MS1-level intensity) / UPS2_SC (spectral counts) represents a data.frame containing the columns "run_id" (freetext), "protein_id" (freetext), "peptide_id" (freetext), "peptide_sequence" (unmodified, natural amino acid sequence in 1-letter nomenclature), "precursor_charge" (positive integer value), "peptide_intensity" (positive non-logarithm floating value) and "concentration" (calibration: positive non-logarithm floating value, prediction: "?"). It should be noted, that the spectral count value is also represented by "peptide_intensity".

See Also

import, ProteinInference, AbsoluteQuantification, ALF, APEX, apexFeatures, proteotypic

Examples