The full proteomics analysis of a small tumor sample (similar in mass to a few grains of rice) produces well over 500 megabytes of unprocessed "raw" data when analyzed on a mass spectrometer (MS). Thus, for every proteomics experiment there is a vast amount of raw data that must be analyzed and interrogated in order to extract biological information. Moreover, the raw data output from different MS vendors are generally in different formats inhibiting the ability of labs to productively work together. Turning this mountain of data into biological insight requires software tools that can analyze and compare the raw data across different platforms. Skyline is one such open-source tool being utilized by investigators throughout the proteomics community and also in NCI's Clinical Proteomic Technology Assessment for Cancer network (CPTAC) to enable the analysis of proteomics data.
Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) experiments. SRM experiments use capabilities of mass spectrometers to selectively monitor peptides and small molecules in order to both determine presence and also quantify amount. Skyline allows investigators to handle, manage and interpret raw data from SRM experiments. As Director of Proteomics, Jim Langridge at Waters states that, "the flexible and intuitive interface that Skyline provides allows the rapid development of peptide MRM assays, overcoming a significant bottleneck."
Recently, the developers of Skyline and its open-source parent project, ProteoWizard, have announced that they have reached a licensing agreement with several MS vendors including: Thermo Fisher Scientific, Waters, AB Sciex, and Agilent Technologies, additionally discussions are currently ongoing with Bruker. These agreements allow Skyline users to directly access the raw mass spectrometry data points, including mass/charge ratios, times, and intensities from data files generated by each of these instrument manufactures. Skyline users can import file formats from different MS vendors, which will improve the ability of researchers to share both methodology and data across instrument platforms. These data are also now accessible to other developers of non-commercial software, through the ProteoWizard data access library.
The ProteoWizard project contains a robust set of modular and extensible open-source, cross-platform tools and libraries to facilitate proteomics data analysis, including Skyline. Initially developed by Darren Kessner within the University of Southern California's Center for Applied Molecular Medicine (CAMM), the ProteoWizard project has grown to include key code contributions from Software developer Matt Chambers, from Dr. Dave Tabb's lab (Vanderbilt University), Brendan Maclean, from Dr. Michael MacCoss' lab (University of Washington), several members of Parag Mallick's lab (Stanford University) and dozens of other developers around the world. Recently, the University of Southern California's CAMM initiated the ProteoWizard Software Foundation, a not-for-profit foundation that has allowed vendors to develop licensing agreements with a legal organization representing the entire academic proteomics community, a key step in allowing the access agreements.
Instrument vendors have noted the value of the interoperability with Skyline and the value it has to their products as well. Dr. Lydia Nuwaysir from AB Sciex, indicates that some of their customers actually prefer Skyline over other products because of its unique features and its ability to be cross-vendor compatible. The cross-vendor compatibility and the integration within current workflows have led Skyline to become a staple in the analysis process for several of the multi-institutional research projects for CPTAC, and the relationship has truly been symbiotic. As Dr. Michael MacCoss, the lead investigator in developing Skyline, states "CPTAC would test and then provide feedback, so it helped to push the product development and helped with buy-in from the research community.
Researchers from both CPTAC and the wider research network have recognized the quick response times with regard to support, the easy exchange of experimental results, and the fact that the source code is open and free. As Dr. Susan Abbatiello from the Broad Institute CPTAC Center comments, "{Skyline} is easy to learn and provides all of the tools necessary to design and execute a targeted, quantitative study of peptide and protein biomarker candidates." The effectiveness and the ease of use have driven many users to not only use it but also provide positive feedback. Dr. Scott Peterman (Thermo Fisher Scientific) describes Skyline as "an invaluable asset to scientist for the advancement of mass spectrometry-based protein quantitation assays." These positive attributes have led to many laboratories and research groups using Skyline on a regular basis and currently, the program is started over 4000 times a month according to activity statics.
With several agreements involving MS vendors, the number of users will likely continue to grow. The next phase of development for Skyline is to leverage the ability to import raw data from the various MS vendors to extend software capabilities. Brendan MacLean, the lead software developer, stated that some of the major areas of development include: "The ability to handle full-scan MS/MS data; accurate mass data, the ability to code samples so that the software will know when a quality control sample or experimental sample is being used, and an increased amount of information related to the entire experiment." Additionally, as computational or software needs arise in the community the Skyline development team intends to respond to implement necessary or innovative changes to empower the research community. These additions should increase functionality and support of researchers in the proteomics field assisting proteomics researchers. Understanding the mountain of data produced from SRM proteomics experiments is easier now due to Skyline and hopefully this will assist efforts to better understand biology and in turn cancer.
More information and downloads of software from the MacCoss Lab are available on the website