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我需要在 35 行（在微阵列中）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。由于我不想手动输入全部 150，我想使用 makeContrast。

我的数据是这样的：

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)

如何获得“RAL517-ZI50”、“RAL852-ZI50”、“RAL517-ZI42”、“RAL852-ZI42”等对比度？

无论如何我可以做到这一点吗？

这些来自我的 sessionInfo()：

> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] C

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] gplots_2.12.1      reshape2_1.2.2     ggplot2_0.9.3.1    affy_1.38.1        vsn_3.28.0         Biobase_2.20.1    
[7] BiocGenerics_0.6.0 limma_3.16.8      

loaded via a namespace (and not attached):
 [1] BiocInstaller_1.10.4  KernSmooth_2.23-10    MASS_7.3-29           RColorBrewer_1.0-5    affyio_1.28.0        
 [6] bitops_1.0-6          caTools_1.14          colorspace_1.2-4      dichromat_2.0-0       digest_0.6.3         
[11] gdata_2.13.2          grid_3.0.2            gtable_0.1.2          gtools_3.1.0          labeling_0.2         
[16] lattice_0.20-23       munsell_0.4.2         plyr_1.8              preprocessCore_1.22.0 proto_0.3-10         
[21] scales_0.2.3          stringr_0.6.2         tools_3.0.2           zlibbioc_1.6.0

谢谢

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1 回答 1

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由于您有两个类之间的类比较问题，我建议您阅读 Bioconductor 的 limma 包的用户指南，这是一个用于识别差异表达基因的流行包（http://www.bioconductor.org/packages/发布/bioc/vignettes/limma/inst/doc/usersguide.pdf）。如果您正在使用单色微阵列，您可以专注于第 9.2 节。

顺便说一句，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")

请注意，表达式矩阵中的样本和因子中的样本标签的顺序相同。为避免此类问题，我建议您创建一个 ExpressionSet 对象（http://www.bioconductor.org/packages/release/bioc/html/Biobase.html），该对象对于操作基因表达数据非常有用。

我希望这可以帮到你，

最好的。

马泰奥

于 2014-04-17T16:01:46.377 回答