R 在两组不同的数据之间进行对比

我需要在35个品系（微阵列）之间找到差异表达的基因。30行名称以RAL开头，5行名称以ZI开头。我想在30条RAL线和5条ZI线之间进行对比。因为我不想手动输入所有150个字符，所以我想使用makeContrast

我的数据如下：

dput(sampletype)

structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 
5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 
10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 
14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 
19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 
23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 
27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 32L, 
32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L), .Label = c("RAL307", 
"RAL820", "RAL705", "RAL765", "RAL852", "RAL799", "RAL301", "RAL427", 
"RAL437", "RAL315", "RAL357", "RAL304", "RAL391", "RAL313", "RAL486", 
"RAL380", "RAL859", "RAL786", "RAL399", "RAL358", "RAL360", "RAL517", 
"RAL639", "RAL732", "RAL379", "RAL555", "RAL324", "RAL774", "RAL42", 
"RAL181", "ZI50N", "ZI186N", "ZI357N", "ZI31N", "ZI197N"), class = "factor")

design.matrix <- model.matrix(~ 0 + sample types)

---

谢谢

由于您在两个类别之间存在类别比较问题，我建议您阅读Bioconductor的limma软件包的用户指南，该软件包是一个用于识别差异表达基因的流行软件包（）。如果您正在使用单色微阵列，则可以关注第9.2节

顺便说一下，您必须创建一个两级因子来执行比较：

# build the design matrix

library(limma)

yourfactor <- c(rep("RAL", 30),rep("ZI", 5))
design <- model.matrix(~ 0 + yourfactor)
colnames(design) <- gsub("yourfactor", "", colnames(design)) # to simplify the colnames of design

# perform the comparison


fit <- lmFit(data, design)    # data is your gene expression matrix
contrast.matrix <- makeContrasts(RAL-ZI, levels=design)
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)

# summarize the results of the linear model
results <- topTable(fit2, number=nrow(data), adjust.method="BH")

#构建设计矩阵
图书馆（林玛）
你的因素
# build the design matrix

library(limma)

yourfactor <- c(rep("RAL", 30),rep("ZI", 5))
design <- model.matrix(~ 0 + yourfactor)
colnames(design) <- gsub("yourfactor", "", colnames(design)) # to simplify the colnames of design

# perform the comparison


fit <- lmFit(data, design)    # data is your gene expression matrix
contrast.matrix <- makeContrasts(RAL-ZI, levels=design)
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)

# summarize the results of the linear model
results <- topTable(fit2, number=nrow(data), adjust.method="BH")