Format

Send to

Choose Destination
Bioinformatics. 2014 Sep 1;30(17):2511-3. doi: 10.1093/bioinformatics/btu200. Epub 2014 Apr 20.

aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data.

Author information

1
Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.
2
Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.

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).

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
24753486
PMCID:
PMC4147881
DOI:
10.1093/bioinformatics/btu200
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center