生信菜鸟团 » T检验 http://www.bio-info-trainee.com 欢迎去论坛biotrainee.com留言参与讨论，或者关注同名微信公众号biotrainee Sat, 28 Jun 2025 14:30:13 +0000 zh-CN hourly 1 https://wordpress.org/?v=4.1.33 用R语言批量做T检验 http://www.bio-info-trainee.com/899.html http://www.bio-info-trainee.com/899.html#comments Tue, 21 Jul 2015 01:06:22 +0000 http://www.bio-info-trainee.com/?p=899 Continue reading →]]> 需要做T检验的的数据如下：其中加粗加黑的是case，其余的是control，需要进行检验的是

p_ma    p_mg    p_ag    p_mag 这四列数据，在case和control里面的差异，当然用肉眼很容易看出，control要比case高很多

 

individual m a g ma mg ag mag p_ma p_mg p_ag p_mag
HBV10-1 33146 3606 2208 308 111 97 39 0.79% 0.29% 0.25% 0.10%
HBV15-1 23580 10300 3140 1469 598 560 323 4.19% 1.71% 1.60% 0.92%
HBV3-1 107856 26445 15077 4773 2383 1869 1130 3.34% 1.67% 1.31% 0.79%
HBV4-1 32763 6448 4384 579 291 295 124 1.35% 0.68% 0.69% 0.29%
HBV6-1 122396 6108 7953 911 796 347 144 0.67% 0.59% 0.26% 0.11%
IGA-1 31337 22167 14195 3851 2752 4101 2028 6.50% 4.65% 6.92% 3.42%
IGA-10 6713 9088 12801 2275 2470 4284 1977 10.54% 11.44% 19.85% 9.16%
IGA-11 61574 23622 15076 5978 4319 3908 2618 6.71% 4.84% 4.38% 2.94%
IGA-12 38510 23353 20148 6941 6201 6510 4328 10.38% 9.27% 9.73% 6.47%
IgA-13 155379 81980 65315 26055 20085 17070 10043 10.38% 8.00% 6.80% 4.00%
IgA-14 345430 86462 71099 27541 21254 10923 6435 6.06% 4.67% 2.40% 1.42%
IgA-15 3864 3076 1942 378 207 389 145 4.66% 2.55% 4.80% 1.79%
IgA-16 3591 4106 2358 427 174 424 114 4.64% 1.89% 4.61% 1.24%
IgA-17 893 1442 799 68 28 78 18 2.27% 0.94% 2.61% 0.60%
IGA-2 23097 5083 5689 910 951 1173 549 2.89% 3.02% 3.72% 1.74%
IGA-3 14058 9364 8565 2130 1953 2931 1436 8.03% 7.36% 11.05% 5.41%
IGA-4 81571 36894 33664 11346 10131 9908 6851 8.86% 7.91% 7.74% 5.35%
IGA-5 27626 6492 4503 963 752 942 410 2.64% 2.06% 2.58% 1.12%
IGA-7 55348 5956 4028 833 476 468 207 1.30% 0.74% 0.73% 0.32%
IGA-8 31671 17097 10443 3894 2666 3514 2003 7.56% 5.17% 6.82% 3.89%

 

但是我们需要写程序对这些百分比在case和control里面进行T检验。

a=read.table("venn_dat.txt",header=T)

type=c(rep("control",5),rep("case",12),"control","control","case")

for (i in 9:12)

{

dat=as.numeric(unlist(lapply(a[i],function(x) strsplit(as.character(x),"%"))))

filename=paste(names(a)[i],".png",sep="")

png(file=filename, width = 320, height = 360)

b=t.test(dat~type)

txt=paste("p-value=",round(b$p.value[1],digits=4),sep="")

plot(as.factor(type),dat,ylab="percent(%)",main=names(a)[i],sub=txt,cex.axis=1.5,cex.sub=2,cex.main=2,cex.lab=1.5)

dev.off()

}

得到的图片如下：

image008

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