现代生物学所需要的现代统计学

看到了一本有意思的书籍：《现代生物学所需要的现代统计学》，名字是我自己翻译的。

主要是因为太多小伙伴在咱们《生信技能树》后台咨询过想不错生物学知识和统计学知识，恰好这个《Modern Statistics for Modern Biology》把二者涵盖了，在线阅读链接：https://www.huber.embl.de/msmb/index.html

全书还配套代码哦：

source("https://www.huber.embl.de/msmb/install_packages.R")


Data

• Zipped data directory，压缩包自己下载，https://www.huber.embl.de/msmb/data.tar.gz

Code

• Rfiles folder，链接是：https://www.huber.embl.de/msmb/code/

章节目录：

• Home
• Book supplements
• Physical Copy
• Introduction
• 1 Generative Models for Discrete Data
• 2 Statistical Modeling
• 3 High Quality Graphics in R
• 4 Mixture Models
• 5 Clustering
• 6 Testing
• 7 Multivariate Analysis
• 8 High-Throughput Count Data
• 9 Multivariate methods for heterogeneous data
• 10 Networks and Trees
• 11 Image data
• 12 Supervised Learning
• 13 Design of High Throughput Experiments and their Analyses
• Statistical Concordance
• Acknowledgements
• References

确实非常详细，图表代码丰富，比如第8节是高通量测序数据表达量矩阵处理：

• Goals of this chapter
• Some core concepts
• Count data
• Modeling count data
• A basic analysis
• Critique of default choices and possible modifications
• Multi-factor designs and linear models
• Generalized linear models
• Two-factor analysis of the pasilla data
• Further statistical concepts
• Summary of this chapter
• Further reading
• Exercises

使用了一个R包《pasilla》里面的果蝇的表达量矩阵和分组信息：

fn = system.file("extdata", "pasilla_gene_counts.tsv",
   package = "pasilla", mustWork = TRUE)
counts = as.matrix(read.csv(fn, sep = "\t", row.names = "gene_id"))
 
annotationFile = system.file("extdata",
  "pasilla_sample_annotation.csv",
  package = "pasilla", mustWork = TRUE)
pasillaSampleAnno = readr::read_csv(annotationFile)
pasillaSampleAnno


然后根据分组，构建好比较信息，使用DESeq2包如下所示代码即可差异分析 ：

library("dplyr")
pasillaSampleAnno = mutate(pasillaSampleAnno,
condition = factor(condition, levels = c("untreated", "treated")),
type = factor(sub("-.*", "", type), levels = c("single", "paired")))
 
library("DESeq2")
pasilla = DESeqDataSetFromMatrix(
  countData = counts,
  colData   = pasillaSampleAnno[mt, ],
  design = ~ condition)
class(pasilla)

pasilla = DESeq(pasilla)

res = results(pasilla)
res[order(res$padj), ] %>% head


是不是超级方便啊！