参考资源:
1.RNA-seq(4):Hisat2+FeatureCounts+DESeq2流程+作图!
https://pzweuj.github.io/2018/07/18/rna-seq-4.html
2.一个植物转录组项目的实战
http://www.bio-info-trainee.com/2809.html
3.RNA_seq(1)植物转录组差异基因分析简单练习
https://www.jianshu.com/p/7146d5c41294
1.Volcano DE 绘图
2.PCA 绘图:
3.Heatmap:实现基因表达模式可视化的需求。 从这里可以看到这4个样本的表达差异,基本是一致的pattern,因为都是拟南芥的rna-seq 样本,no more difference.
Rscript:
library(pheatmap)
select <- order(rowMeans(counts(dds, normalized=T)), decreasing=T)[1:1000]
nt <-normTransform(dds)log2.norm.counts <- assay(nt)[select,]df <- as.data.frame(colData(dds)[, c("name", "condition")])pheatmap(log2.norm.counts, cluster_rows=T, show_rownames=F, cluster_cols=T, annotation_col=df, fontsize=6)
网友评论