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使用WLSplot轻松绘制蠕虫寿命并进行统计分析。

Easy Worm Lifespan Plotting and Statistics with WLSplot.

作者信息

Mariner Blaise L, Peterson Jack, Taylor Jackson C, Achusim Alex T, McCormick Mark A

机构信息

Biochemistry and Molecular Biology, University of New Mexico, Albuquerque, New Mexico, United States.

Chemical and Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico, United States.

出版信息

MicroPubl Biol. 2023 Oct 2;2023. doi: 10.17912/micropub.biology.000991. eCollection 2023.

DOI:10.17912/micropub.biology.000991
PMID:37854099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10580078/
Abstract

WLSplot is an R package used to easily analyze lifespan survival data, and display results graphically as a survival curve with useful labels and statistical information auto-generated from the data and added to the graph, within a single function. It is designed primarily with lifespan data in mind initially but can easily be used for other types of survival data. The WLSplot GitHub repository provides a blank template spreadsheet to be used for collecting lifespan data, instructions on how to install and run WLSplot, and examples covering RNAi, Genotype, or Drug lifespan experimental set-ups. WLSplot can analyze and plot multiple experiments in bulk while correctly italicizing worm gene names and adding asterisks and p-values to the plot legend when a significantly different lifespan from the designated control lifespan is seen. This is returned as an editable scalable vector graphics (svg) file for each output, and WLSplot can also return the summary of the directly plotted data so that the researcher can do their own further manipulation, in addition to being able to edit the output svg files.

摘要

WLSplot是一个R软件包,用于轻松分析寿命生存数据,并在单个函数中以生存曲线的形式图形化显示结果,该曲线带有从数据自动生成并添加到图形中的有用标签和统计信息。它最初主要是为寿命数据设计的,但也可以轻松用于其他类型的生存数据。WLSplot的GitHub存储库提供了一个用于收集寿命数据的空白模板电子表格、关于如何安装和运行WLSplot的说明,以及涵盖RNA干扰、基因型或药物寿命实验设置的示例。WLSplot可以批量分析和绘制多个实验,同时正确地将线虫基因名称斜体显示,并在观察到与指定对照寿命有显著差异的寿命时,在绘图图例中添加星号和p值。每个输出都会返回一个可编辑的可缩放矢量图形(svg)文件,WLSplot还可以返回直接绘制数据的摘要,以便研究人员除了能够编辑输出的svg文件外,还可以进行自己的进一步操作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d89/10580078/d4cf6257df6b/25789430-2023-micropub.biology.000991.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d89/10580078/d4cf6257df6b/25789430-2023-micropub.biology.000991.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d89/10580078/d4cf6257df6b/25789430-2023-micropub.biology.000991.jpg

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