法国里昂第一大学Mirko Francesconi研究组利用RAPToR从转录组中预测真实年龄。这一研究成果于2022年7月11日在线发表在国际学术期刊《自然—方法学》上。

研究人员提出了从参考转录组分期的真实年龄预测（RAPToR），这是一种计算方法，利用现有的时间序列数据作为参考，从样本的转录组精确估计其真实年龄。RAPToR适用于最常见的动物模型、人类的全动物、解剖组织和单细胞数据，甚至适用于缺乏参考数据的非模型生物体。结果表明，RAPToR可以用来消除年龄这一混杂因素，并允许在差异表达分析中恢复一个感兴趣的信号。RAPToR将在大规模的单生物体分析中特别有用，因为它消除了在分析前的精确分期或同步化的需要。

据介绍，转录组数据经常受到样本之间不受控制的变异的影响，这种变异会掩盖和混淆感兴趣的效果。这种变异经常是由于样本之间发展阶段的非故意差异造成的。转录组本身可以用来估计发育进程，但现有的方法需要许多样本，而且不能估计一个标本的真实年龄。

附：英文原文

Title: Real age prediction from the transcriptome with RAPToR

Author: Bulteau, Romain, Francesconi, Mirko

Issue&Volume: 2022-07-11

Abstract: Transcriptomic data is often affected by uncontrolled variation among samples that can obscure and confound the effects of interest. This variation is frequently due to unintended differences in developmental stages between samples. The transcriptome itself can be used to estimate developmental progression, but existing methods require many samples and do not estimate a specimen’s real age. Here we present real-age prediction from transcriptome staging on reference (RAPToR), a computational method that precisely estimates the real age of a sample from its transcriptome, exploiting existing time-series data as reference. RAPToR works with whole animal, dissected tissue and single-cell data for the most common animal models, humans and even for non-model organisms lacking reference data. We show that RAPToR can be used to remove age as a confounding factor and allow recovery of a signal of interest in differential expression analysis. RAPToR will be especially useful in large-scale single-organism profiling because it eliminates the need for accurate staging or synchronisation before profiling.

DOI: 10.1038/s41592-022-01540-0

Source: https://www.nature.com/articles/s41592-022-01540-0