Philosopher: a versatile toolkit for shotgun proteomics data analysis

To the Editor — Here we introduce Philosopher (https://philosopher.nesvilab. org), a free, open-source, versatile and robust data analysis toolkit designed to bring easy access to a powerful and comprehensive set of computational tools for shotgun proteomics data analysis. Computational analysis is a central component of any modern experiment, and mass-spectrometry-based proteomics is no exception. As technologies continue to rapidly advance with respect to throughput and sensitivity, bioinformatics tools must keep pace with large-scale experiments. While existing proteomics tools such as the Trans-Proteomic Pipeline (TPP)1, MaxQuant2 and PeptideShaker3 are capable of performing high-quality analyses, all require installation and depend on specific operating systems, libraries and other software. Managing these tools can be a daunting task, even for research groups with substantial bioinformatics expertise. This is particularly true when experiments demand high-performance configurations such as GNU/Linux clusters or cloud computing. To address this challenge, we initially built and deployed Docker containers with different applications for proteomics, which in part inspired the creation of the BioContainers resource for different bioinformatics fields4. Though this method was efficient for packing and sharing resources, we found that chaining different applications with custom implementation of established algorithms in a transparent and dependency-free way was still a challenge for containerization. The Philosopher toolkit integrates high-performance algorithms and existing tools (Fig. 1) and is a dependency-free, fast and comprehensive proteomics pipeline, able to rapidly process even the most complex proteomics datasets with efficient resource management. Philosopher includes the database search engine Comet and can use the high-performance search engine MSFragger5 as a separately downloaded tool. For downstream processing of peptide– spectrum matches (PSMs), Philosopher includes key components of TPP. In addition, it implements best practices for false discovery rate (FDR) filtering and data summarization that are not readily available within the TPP, such as picked FDR, two-dimensional or sequential (at PSM and protein levels) filters, and additional options for dealing with peptides whose sequence is present in multiple proteins (for example, the razor peptide approach). As quantification is frequently the goal of modern proteomics experiments, Philosopher includes algorithms for both label-free quantification and isobaric label-based quantification (TMT or iTRAQ). Precursor spectral intensities are retrieved following a method described previously6. Protein-level quantification is estimated using the sum of the three most intense supporting ions. Alternatively, Philosopher can use TMT-Integrator (http://tmt-integrator.nesvilab.org/) as an external tool or output files can be used with downstream quantification and statistical tools such as MSstats7. The rich reports generated by Philosopher are also compatible with other software such as PDV for visualization of peptide assignments to tandem mass spectra8 and CRAPome and REPRINT (https://reprint-apms. org/) for interactome scoring and network