Spectronaut软件

仪器介绍
Spectronaut 是一款进行 DIA(Data-independent acquisition,数据非依赖采集)数据分析的商业化软件,为 DIA 数据的分析提供完整的解决方案,包括谱图库构建、数据质控、蛋白定量、统计分析、GO 富集等。可实现大规模实验的快速分析,最多可实现高达 10,000 个 run 的分析。具有良好的交互体验,便于初学者上手,行业深耕者也可按需优化各项设置,达到分析目的,实现数据高质解析。
参数
Spectral library construction | • Comes with the Pulsar search engine, supporting DDA, DIA, and PRM (including MS1 information) for building high-quality libraries; • Supports external search engines, including Proteome Discoverer, MaxQuant, ProteinPilot, and Mascot search results for library construction; • Deep learning-assisted iRT retention time correction, decoy prediction, and Pulsar scoring further enhance peptide identification quantity. |
DIA data analysis | • Supports DIA analysis based on spectral libraries; • Supports non-library-dependent directDIA analysis; • Computer deep learning enhances spectral-centered DIA data analysis performance, with directDIA+ identification quantity significantly improved (Version 17.0). Compared to SN16, identification depth can increase by 50% to 100% for different acquisition types, and offers FAST and DEEP modes for user selection. |
Support for ion mobility | • Fully compatible with PASEF, FAIMS Pro, and HDMS2: • Improved algorithms for predicting retention time and ion mobility (Version 17.0); • Supports 1F Slice dia-PASEF data analysis (Version 17.0); • Supports PTM DIA data analysis; • Supports label-free quantification analysis (up to 3 channels). |
Data quality control | Data quality control module reliant on iRT kit, performing quality control on DIA data analysis regarding mass-to-charge ratio, retention time, signal intensity, etc. |
SNE integration | Addresses large dataset analysis. Allows splitting large datasets into multiple sub-datasets for individual analysis and generating SNE files, which can then be merged in the Pipeline view to output a comprehensive report. |
Statistical and bioinformatics analysis | • Identification depth statistics; • Identification score statistics; • Sample coefficient of variation analysis; • Sample correlation analysis; • Sample and protein clustering analysis; • Differential protein analysis; • Differential protein volcano plots; • Protein GO functional annotation and enrichment analysis. |
Report output | • Comprehensive report content; • Supports personalized report customization. |