转录组原始count矩阵DESeq2差异表达分析
简介
本模块调用DESeq2对转录组原始表达矩阵(count)进行标准化,并执行差异表达分析。
输入数据
输入为原始count的表达矩阵。行是基因,列是样品,count必需是正整数,可以为0,但是不能为空或者NA。首列是基因名,必需唯一;其他列为每个样品的count,样品名必需唯一。
论文例子
Differential gene expression analysis based on the negative binomial distribution
示例
|
示例数据
|
输出 |
1,表达谱,raw count+ normalized count。可以提取具体基因的标准化表达值,(加1,并log2转化后)绘制热图
2,指定比较的差异总表,请使用excel自行过滤挑选差异表达基因
|
如何引用?
建议直接写网址。4400+篇
google学术,3700+篇
知网学术
正式引用:Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, Wu S, Wang Y.
SRplot: A free online platform for data visualization and graphing. PLoS One. 2023 Nov 9;18(11):e0294236. doi: 10.1371/journal.pone.0294236. PMID: 37943830.
方法章节:Heatmap was plotted by https://www.bioinformatics.com.cn (last accessed on 10 Oct 2024), an online platform for data analysis and visualization.
致谢章节:We thank Mingjie Chen (Shanghai NewCore Biotechnology Co., Ltd.) for providing data analysis and visualization support.