小柯机器人

美国Calico生命科学公司Fiona E. McAllister等研究人员合作发现，结合多个批次的数据分析框架可提高同位素蛋白质组学实验的能力。该研究于2023年12月18日在线发表于国际一流学术期刊《自然—方法学》。

附：英文原文

Title: A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments

Author: OBrien, Jonathon J., Raj, Anil, Gaun, Aleksandr, Waite, Adam, Li, Wenzhou, Hendrickson, David G., Olsson, Niclas, McAllister, Fiona E.

Issue&Volume: 2023-12-18

Abstract: We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.

DOI: 10.1038/s41592-023-02120-6

Source: https://www.nature.com/articles/s41592-023-02120-6

Nature Methods：《自然—方法学》，创刊于2004年。隶属于施普林格·自然出版集团，最新IF：47.99
官方网址：https://www.nature.com/nmeth/
投稿链接：https://mts-nmeth.nature.com/cgi-bin/main.plex