计算机科学
工作流程
杠杆(统计)
Python(编程语言)
碎片(计算)
积分器
错误发现率
软件
数据库搜索引擎
数据挖掘
搜索引擎
情报检索
数据库
人工智能
操作系统
基因
化学
生物化学
带宽(计算)
计算机网络
作者
Brian C. Searle,Ariana E. Shannon,Damien B. Wilburn
标识
DOI:10.1021/acs.jproteome.2c00672
摘要
Spectrum library searching is a powerful alternative to database searching for data dependent acquisition experiments, but has been historically limited to identifying previously observed peptides in libraries. Here we present Scribe, a new library search engine designed to leverage deep learning fragmentation prediction software such as Prosit. Rather than relying on highly curated DDA libraries, this approach predicts fragmentation and retention times for every peptide in a FASTA database. Scribe embeds Percolator for false discovery rate correction and an interference tolerant, label-free quantification integrator for an end-to-end proteomics workflow. By leveraging expected relative fragmentation and retention time values, we find that library searching with Scribe can outperform traditional database searching tools both in terms of sensitivity and quantitative precision. Scribe and its graphical interface are easy to use, freely accessible, and fully open source.
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