Abstract
Motivation: The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking.Results: We present a bioinformatics tool, termed aLFQ, which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation.Availability and implementation: aLFQ is written in R and freely available under the GPLv3 from CRAN (http://www.cran.r-project.org). Instructions and example data are provided in the R-package. The raw data can be obtained from the PeptideAtlas raw data repository (PASS00321).Contact: lars.malmstroem@imsb.biol.ethz.chSupplementary information: Supplementary data are available at Bioinformatics online.
Highlights
A variety of quantitative proteomic methods have been established to measure the relative abundance of proteins across samples
The current gold standard for LC-MS/MS–based absolute protein quantification is the use of stable isotope-labeled standard (SIS) peptides or proteins in precisely determined concentrations (Brun et al, 2009). These standards are spiked into the biological sample of interest and the absolute concentration of the endogenous peptides, and proteins can directly be determined by calculating the ratio of the measured intensities of the spikedin heavy and the endogenous light forms
Relative quantification methods are useful to compare the same proteins between multiple biological samples, they do not provide the possibility to directly compare the data with other datasets or compare different proteins within a dataset with each other and they, by definition, do not provide absolute quantitative data
Summary
A variety of quantitative proteomic methods have been established to measure the relative abundance of proteins across samples. These standards are spiked into the biological sample of interest and the absolute concentration of the endogenous peptides, and proteins can directly be determined by calculating the ratio of the measured intensities of the spikedin heavy and the endogenous light forms. What these methods have in common is that they either use the linear log–log correlation between absolute protein abundance and experimentally estimated protein intensity or an estimate of the total protein concentration of the sample.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
