大多数统计学导论课程和书籍基本覆盖了实验设计。Experimental Design and Data Analysis for Biologists 2002是关于这个话题非常优秀的书籍。Chapter 18 of O’Reilly’s Statistics in a Nutshell, 2nd Edition也是一个很好的参考。不过,请注意, 基因组学实验中的实验设计是另一回事,正在积极研究和改进。确保...
现代软件如R的 Knitr和iPython Notebooks是记录研究的强大工具;我在本章的GitHub README中列出了一些开始使用这些工具的资源。 把脚本的运行结果制作成图像或者统计结果 要确保一个科学项目是可重复的,不仅涉及对关键统计检验的可重复性,支持科学发现的要素(如图表)也应是可重复的。确保这些要素可重复的最佳方法是让...
通过数据的完整性也有利于研究的可重现,可以使用文件校验和来作为数据版本(git commit ID)。 这里我们介绍一下数据完整性检验和SHA-1与MD5的使用以及对比文件区别的命令。 SHA与MD5 SHA-1与MD5码是非常类似的,前者出现更晚也更倾向于被采用(Github就是使用SHA-1码作为commit ID)。 相同的内容计算得到的SHA-1码...
生物信息学技能提升,专注于工具使用与编程. Contribute to Ming-Lian/Bioinformatics-skills development by creating an account on GitHub.
bds-files, 我的书的补充文件,"Bioinformatics Data Skills" 生物信息学数据技能补充材料库这个库包含我的书中使用的补充文件,生物信息学数据技能( ),由 O'Reilly 媒体发布。 除了本书中示例所需的补充文件外,这里知识库还包含:关于如何生成所有补充文件或者如何获取这些文件的文档。其 ...
Places likeStackOverflowandGitHub’s issue tracking on specific open source software packagesare great for finding helpful answers to problems if you cannot find relevant information elsewhere. Don’t be afraid to post on public forums. This is also a great way to interact with the authors of op...
Availability of data and materials The software Single-cell Spatial Explorer is available on github The human prostate cancer dataset was downloaded from 10x Genomics website (https://www.10xgenomics.com/resources/datasets/human-prostate-cancer-adjacent-normal-section-with-if-staining-ffpe-1-standard-...
We used a clustering approach to identify a sequence set that could provide an optimal trade-off between potential missing data and probe set cost. We incorporated this probe set into a user-friendly wrapper script named UnFATE (https://github.com/claudioametrano/UnFATE) that allows ...
[17]. We implemented the source code available athttps://github.com/dansondergaard/tmhmm.pyadapting it to work with thousands of FASTA protein sequences.TMhelicespredicts, for each protein, the number of transmembrane helices domains (TMDn), as well as”Tmhmm seq”, a reduced-alphabet protein...
[17]. We implemented the source code available athttps://github.com/dansondergaard/tmhmm.pyadapting it to work with thousands of FASTA protein sequences.TMhelicespredicts, for each protein, the number of transmembrane helices domains (TMDn), as well as”Tmhmm seq”, a reduced-alphabet protein...