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PTM-Shepherd is a bioinformatics tool that automates characterization of PTM profiles detected in open searches based on attributes such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multi-experiment comparisons for studying changes in modification profiles, e.g. in data generated in different laboratories or under different conditions. PTM-Shepherd has recently been expanded to included glycan assignment with multi-attribute FDR scoring and diagnostic feature extraction.
We strongly recommend running PTM-Shepherd via FragPipe to simplify open search analysis. PTM-Shepherd can also be run from the command line as a standalone JAR file.
- You can downlaod the latest Fragpipe release here.
- You can download the latest standlone release of PTM-Shepherd here.
PTM-Shepherd requires two pieces of data as input: filtered PSM lists and spectral files. Filtered PSM lists are produced by Philosopher. The following spectral file formats can be process directly with PTM-Shepherd, see the FragPipe homepage for compatibility with other workflow components.
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mzML/mzXML - data from any instrument in mzML/mzXML format can be used
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Thermo RAW - Thermo raw files (.raw) can be read directly, conversion to mzML is not required
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Bruker timsTOF PASEF - PTM-Shepherd can read Bruker timsTOF PASEF (DDA) raw files (.d) that have been processed by MSFragger, as well as MGF files converted by the Bruker DataAnalysis program.
PTM-Shepherd can requires substantial amounts of memory for some analyses on large datasets (particularly diagnostic ion mining). Most standard analyse can be completed with 4 GB of memory. The processor requirements of PTM-Shepherd are modest unless doing diagnostic ion mining. It frequently runs in under a minute for standard analyses on most laptops.
PTM-Shepherd has been tested on Windows 7, Windows 10, Windows 11, and a number of Linux distributions. Note that a 64-bit operating system is required to access more than 4 GB of memory.
PTM-Shepherd is written using Java 10.0.1 and requires a Java 9+ Runtime Environment. We recommend the Oracle Runtime Environment (download and installation instructions are available at www.java.com).
Daniel J. Geiszler, Andy T. Kong, Dmitry M. Avtonomov, Fengchao Yu, Felipe V. Leprevost, Alexey I. Nesvizhskii. PTM-Shepherd: analysis and summarization of post-translational and chemical modifications from open search results. doi: (https://doi.org/10.1074/mcp.TIR120.002216)[https://doi.org/10.1074/mcp.TIR120.002216].
Daniel A. Polasky, Daniel J. Geiszler, Fengchao Yu, Alexey I. Nesvizhskii. Multiattribute Glycan Identification and FDR Control for Glycoproteomics. doi: (https://doi.org/10.1016/j.mcpro.2022.100205)[https://doi.org/10.1016/j.mcpro.2022.100205].
Daniel J. Geiszler, Daniel A. Polasky, Fengchao Yu, Alexey I. Nesvizhskii. Mining for ions: diagnostic feature detection in MS/MS spectra of post-translationally modified peptides. doi: (https://doi.org/10.1101/2022.09.12.507594)[https://doi.org/10.1101/2022.09.12.507594].