Straightforward Filtering Index for AP-MS Data Analysis (SFINX)

The straightforward filtering index (SFINX) identifies true positive protein interactions in a fast, user-friendly, and highly accurate way. It is not only useful for the filtering of affinity purification - mass spectrometry (AP-MS) data, but also for similar types of data resulting from other co-complex interactomics technologies, such as TAP-MS, Virotrap and BioID. SFINX can also be used via the website interface at < http://sfinx.ugent.be>.


Affinity purification-mass spectrometry is one of the most common techniques for the analysis of protein-protein interactions, but inferring bona fide interactions from the resulting data sets remains notoriously difficult. We introduce SFINX, a Straightforward Filtering INdeX that identifies true-positive protein interactions in a fast, user-friendly, and highly accurate way. SFINX outperforms alternative techniques on benchmark data sets and is also available via the Web interface at http://sfinx.ugent.be/.

The analysis of protein-protein interactions enables scientists to connect genotypes with phenotypes and to answer fundamental biological questions or generate new hypotheses on the functions of proteins. In this field, affinity purification-mass spectrometry is a classical approach wherein a protein of interest (bait) containing an epitope tag is purified under conditions that preserve the protein complex to allow the identification of co-purifying proteins by mass spectrometry.

Several software approaches already exist to separate the false-positives from the true-positives in these protein-protein interaction data sets, but none of these approaches combines high accuracy, speed and user-friendliness without the need for the input of external data. Therefore, we developed the Straightforward Filtering INdeX (SFINX), which excels at all these points.

Users can easily access SFINX via the Web site interface at http://sfinx.ugent.be/ or via this package. This package also allows users to more easily integrate SFINX in their own R pipelines or on their own servers.

You can install the released version of the package from CRAN using:

install.packages("sfinx")

To use the sfinx package that you installed in your library, you also have to load it as follows:

library(sfinx)

You can perform the standard SFINX analysis by using the sfinx() function of this package.

sfinx(DataInputExampleFile, BaitIdentityExampleFile)

Kevin Titeca

Further information and examples can be found in the sfinx-vignette file and by accessing the document information as follows:

?sfinx
 
help(sfinx)

The SFINX algorithm and its interface were published in the Journal of Proteome Research on January 4, 2016.

SFINX: Straightforward Filtering Index for Affinity Purification-Mass Spectrometry Data Analysis. Kevin Titeca, Pieter Meysman, Kris Gevaert, Jan Tavernier, Kris Laukens, Lennart Martens, and Sven Eyckerman. Journal of Proteome Research 2016 15 (1), 332-338. DOI: 10.1021/acs.jproteome.5b00666.

If you have suggestions or questions that remain after reading the article, the manual and the object information, you can contact us at sfinxinteractomics@gmail.com .

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Reference manual

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install.packages("sfinx")

1.7.9 by Kevin Titeca, 2 months ago


http://sfinx.ugent.be


Browse source code at https://github.com/cran/sfinx


Authors: Kevin Titeca [aut, cre], Jan Tavernier [ths], Sven Eyckerman [ths]


Documentation:   PDF Manual  


Apache License 2.0 license


Suggests knitr, rmarkdown, testthat


See at CRAN