UPS2MS: Calculating absolute and relative protein abundance from mass...

Description Usage Format See Also Examples

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

1

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

1

Example output



aLFQ documentation built on Jan. 8, 2020, 5:09 p.m.

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