脂质体
脂类学
计算机科学
可视化
软件
数据可视化
计算生物学
数据挖掘
生物信息学
数据库
生物
程序设计语言
作者
Peter Husen,Kirill V. Tarasov,Maciej Katafiasz,Elena Sokol,Jürgen Vogt,Jan Baumgart,Robert Nitsch,Kim Ekroos,Christer S. Ejsing
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2013-11-07
卷期号:8 (11): e79736-e79736
被引量:135
标识
DOI:10.1371/journal.pone.0079736
摘要
Global lipidomics analysis across large sample sizes produces high-content datasets that require dedicated software tools supporting lipid identification and quantification, efficient data management and lipidome visualization. Here we present a novel software-based platform for streamlined data processing, management and visualization of shotgun lipidomics data acquired using high-resolution Orbitrap mass spectrometry. The platform features the ALEX framework designed for automated identification and export of lipid species intensity directly from proprietary mass spectral data files, and an auxiliary workflow using database exploration tools for integration of sample information, computation of lipid abundance and lipidome visualization. A key feature of the platform is the organization of lipidomics data in "database table format" which provides the user with an unsurpassed flexibility for rapid lipidome navigation using selected features within the dataset. To demonstrate the efficacy of the platform, we present a comparative neurolipidomics study of cerebellum, hippocampus and somatosensory barrel cortex (S1BF) from wild-type and knockout mice devoid of the putative lipid phosphate phosphatase PRG-1 (plasticity related gene-1). The presented framework is generic, extendable to processing and integration of other lipidomic data structures, can be interfaced with post-processing protocols supporting statistical testing and multivariate analysis, and can serve as an avenue for disseminating lipidomics data within the scientific community. The ALEX software is available at www.msLipidomics.info.
科研通智能强力驱动
Strongly Powered by AbleSci AI