scholarly journals COSS: A fast and user-friendly tool for spectral library searching

2019 ◽  
Author(s):  
Genet Abay Shiferaw ◽  
Elien Vandermarliere ◽  
Niels Hulstaert ◽  
Ralf Gabriels ◽  
Lennart Martens ◽  
...  
Keyword(s):  
Scoring Functions ◽  
Sequence Database ◽  
Spectral Library ◽  
Data Formats ◽  
Large Databases ◽  
Search Tool ◽  
Spectral Searching ◽  
Spectral Libraries ◽  
User Friendly ◽  
Sequence Database Search

ABSTRACTSpectral similarity searching to identify peptide-derived MS/MS spectra is a promising technique, and different spectrum similarity search tools have therefore been developed. Each of these tools, however, comes with some limitations, mainly due to low processing speed and issues with handling large databases. Furthermore, the number of spectral data formats supported is typically limited, which also creates a threshold to adoption. We have therefore developed COSS (CompOmics Spectral Searching), a new and user-friendly spectral library search tool supporting two scoring functions. COSS also includes decoy spectra generation for result validation. We have benchmarked COSS on three different spectral libraries and compared the results with established spectral search and sequence database search tool. Our comparison showed that COSS more reliably identifies spectra and is faster than other spectral library searching tools. COSS binaries and source code can be freely downloaded from https://github.com/compomics/COSS.

scholarly journals Sensitive and specific spectral library searching with COSS and Percolator

2021 ◽  
Author(s):  
Genet Abay Shiferaw ◽  
Ralf Gabriels ◽  
Elien Vandermarliere ◽  
Lennart Martens ◽  
Pieter-Jan Volders
Keyword(s):  
Peptide Identification ◽  
High Sensitivity ◽  
Substantial Improvement ◽  
Mass Spectrometry Data ◽  
Data Sets ◽  
Sequence Database ◽  
Post Processing ◽  
Spectral Library ◽  
False Discovery ◽  
Sequence Database Search

Maintaining high sensitivity while limiting false positives is a key challenge in peptide identification from mass spectrometry data. Here, we therefore investigate the effects of integrating the machine learning-based post-processor Percolator into our spectral library searching tool COSS. To evaluate the effects of this post-processing, we have used twenty data sets from two different projects and have matched these against the NIST spectral library. The matching is carried out using two performant spectral library search engines (COSS and MsPepSearch), both with and without Percolator post-processing, and using sequence database search engine MS-GF+ as a baseline comparator. The addition of the Percolator rescoring step was particularly effective for COSS, resulting in a substantial improvement in sensitivity and specificity of the identifications. Importantly, the false discovery rate was especially strongly affected, resulting in much more reliable results. COSS is freely available as open source under the permissive Apache2 license, and binaries and source code are found at https://github.com/compomics/COSS .

Comet: An open-source MS/MS sequence database search tool

PROTEOMICS ◽  
2012 ◽  
Vol 13 (1) ◽  
pp. 22-24 ◽  
Author(s):  
Jimmy K. Eng ◽  
Tahmina A. Jahan ◽  
Michael R. Hoopmann
Keyword(s):  
Open Source ◽  
Database Search ◽  
Sequence Database ◽  
Search Tool ◽  
Sequence Database Search

scholarly journals Identifying Fentanyl with Mass Spectral Libraries

2021 ◽  
Author(s):  
Anthony J. Kearsley ◽  
Arun Moorthy
Keyword(s):  
Law Enforcement ◽  
Similarity Measures ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Mass Spectral ◽  
Fentanyl Analogs ◽  
Spectral Libraries ◽  
Mass Spectral Libraries

<div> <div> <div> <p>Synthesis, distribution and abuse of fentanyl, a synthetic opioid, has led to a critical worldwide epidemic. Mass spectral library searching for opioids remains unresolved despite being central to law-enforcement involving identification, monitoring and prosecution of opioid related crimes. In this article, two model problems are presented to illustrate difficulties associated with fentanyl identification. A collection of both currently-employed similarity measures and intuitive measures of dissimilarity are employed to simulate identifying fentanyl analogs with mass spectral library searching. </p> </div> </div> </div>

Fast semi-local alignment for DNA sequence database search

2003 ◽  
Author(s):  
Yong-Sheng Chen ◽  
Yi-Ping Hung ◽  
Chiou-Shann Fuh
Keyword(s):  
Dna Sequence ◽  
Database Search ◽  
Local Alignment ◽  
Sequence Database ◽  
Sequence Database Search

scholarly journals COSS: A Fast and User-Friendly Tool for Spectral Library Searching

2020 ◽  
Vol 19 (7) ◽  
pp. 2786-2793
Author(s):  
Genet Abay Shiferaw ◽  
Elien Vandermarliere ◽  
Niels Hulstaert ◽  
Ralf Gabriels ◽  
Lennart Martens ◽  
...  
Keyword(s):  
Spectral Library ◽  
User Friendly

Code Optimization of the Subroutine to Remove Near Identical Matches in the Sequence Database Homology Search Tool PSI-BLAST

2010 ◽  
Vol 17 (6) ◽  
pp. 819-823 ◽  
Author(s):  
Mats Aspnäs ◽  
Kimmo Mattila ◽  
Kristoffer Osowski ◽  
Jan Westerholm
Keyword(s):  
Homology Search ◽  
Code Optimization ◽  
Sequence Database ◽  
Search Tool

scholarly journals FishPathogens.eu/vhsv: a user-friendly viral haemorrhagic septicaemia virus isolate and sequence database

2009 ◽  
Vol 32 (11) ◽  
pp. 925-929 ◽  
Author(s):  
S P Jonstrup ◽  
T Gray ◽  
S Kahns ◽  
H F Skall ◽  
M Snow ◽  
...  
Keyword(s):  
Virus Isolate ◽  
Sequence Database ◽  
Haemorrhagic Septicaemia ◽  
Viral Haemorrhagic Septicaemia Virus ◽  
User Friendly

scholarly journals pChem: a modification-centric assessment tool for the performance of chemoproteomic probes

2021 ◽  
Author(s):  
Ji-Xiang He ◽  
Zheng-Cong Fei ◽  
Ling Fu ◽  
Cai-Ping Tian ◽  
Fu-Chu He ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Protein Profiling ◽  
Metabolic Labeling ◽  
Experimental Setting ◽  
Computational Tool ◽  
On Demand ◽  
Manual Inspection ◽  
Search Tool ◽  
Blind Search ◽  
User Friendly

We report a modification-centric, blind-search tool termed pChem to provide a streamlined pipeline for unbiased assessing of the performance of chemoproteomic probes. The pipeline starts with an experimental setting for isotopically coding probe-derived modifications that can be automatically recognized, accurately calculated and precisely localized by pChem with neither prior knowledge nor manual inspection. Further, pChem exports on-demand reports by scoring the profiling efficiency, modification-homogeneity and proteome-wide residue selectivity of a tested probe. The performance and robustness of pChem were benchmarked by applying it to various bioorthogonal probes, including 15 activity-based protein profiling (ABPP) probes and 3 metabolic labeling probes. Together, pChem is a user-friendly computational tool for probe developers, even those with no experience in informatics, and aims to facilitate the development and optimization of probes for the ever-growing field of chemoproteomics.

Sign in / Sign up

Export Citation Format

Share Document