Aasebø Elise, Berven Frode S, Selheim Frode, Barsnes Harald, Vaudel Marc
Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway.
KG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of Bergen, Bergen, Norway.
Methods Mol Biol. 2016;1394:261-273. doi: 10.1007/978-1-4939-3341-9_19.
In quantitative proteomics, large lists of identified and quantified proteins are used to answer biological questions in a systemic approach. However, working with such extensive datasets can be challenging, especially when complex experimental designs are involved. Here, we demonstrate how to post-process large quantitative datasets, detect proteins of interest, and annotate the data with biological knowledge. The protocol presented can be achieved without advanced computational knowledge thanks to the user-friendly Perseus interface (available from the MaxQuant website, www.maxquant.org ). Various visualization techniques facilitating the interpretation of quantitative results in complex biological systems are also highlighted.
在定量蛋白质组学中,大量已鉴定和定量的蛋白质列表被用于以系统的方法回答生物学问题。然而,处理如此庞大的数据集可能具有挑战性,尤其是当涉及复杂的实验设计时。在这里,我们展示了如何对大型定量数据集进行后处理、检测感兴趣的蛋白质,并利用生物学知识对数据进行注释。由于用户友好的Perseus界面(可从MaxQuant网站www.maxquant.org获得),无需先进的计算知识即可完成本文介绍的方案。还强调了各种有助于解释复杂生物系统中定量结果的可视化技术。