计算机科学
软件
R包
统计分析
仿形(计算机编程)
理论(学习稳定性)
排名(信息检索)
非参数统计
错误发现率
数据挖掘
机器学习
统计
数学
化学
操作系统
程序设计语言
基因
生物化学
作者
Hongchao Ji,Xue Lu,Zhenxiang Zheng,Siyuan Sun,Chris Soon Heng Tan
摘要
The Cellular Thermal Shift Assay (CETSA) plays an important role in drug-target identification, and statistical analysis is a crucial step significantly affecting conclusion. We put forward ProSAP (Protein Stability Analysis Pod), an open-source, cross-platform and user-friendly software tool, which provides multiple methods for thermal proteome profiling (TPP) analysis, nonparametric analysis (NPA), proteome integral solubility alteration and isothermal shift assay (iTSA). For testing the performance of ProSAP, we processed several datasets and compare the performance of different algorithms. Overall, TPP analysis is more accurate with fewer false positive targets, but NPA methods are flexible and free from parameters. For iTSA, edgeR and DESeq2 identify more true targets than t-test and Limma, but when it comes to ranking, the four methods show not much difference. ProSAP software is available at https://github.com/hcji/ProSAP and https://zenodo.org/record/5763315.
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