R语言中miRNA与靶基因相关性作图的示例分析

这篇文章将为大家详细讲解有关R语言中miRNA与靶基因相关性作图的示例分析，小编觉得挺实用的，因此分享给大家做个参考，希望大家阅读完这篇文章后可以有所收获。

miRNA与靶基因相关性作图

首先，要生成作图的输入文件，有脚本，用法如下：

perl  Correlation_analysis.pl  -mirna Donkey_E_vs_Donkey_T.DEG.final.xls  -DE_tar targets.final.xls  -list bta.mir2target.list  -out Correlation_analysis_input.txt

其中Donkey_E_vs_Donkey_T.DEG.final.xls是差异miRNA表达量文件；targets.final.xls是靶基因表达量文件；bta.mir2target.list 是miRNA与靶基因对应文件。

Donkey_E_vs_Donkey_T.DEG.final.xls与targets.final.xls格式相同，如下所示：

#ID     Donkey2_E_Count Donkey1_T_Count Donkey2_E_TPM   Donkey1_T_TPM   FDR     log2FC  regulatedbta-miR-106a    26      113     1.164865        54.990056       3.20268371822863e-08    4.02066488557677        upbta-miR-10a     166025  1771    7438.335738     861.835296      0.000238871249442218    -4.55148673628311       downbta-miR-135a    5631    114     252.2829        55.476693       0.00268305048158635     -3.62181067749427       downbta-miR-135b    25      89      1.120063        43.310752       6.41785537824902e-07    3.73045876228641        upbta-miR-141     1201    2       53.807807       0.973275        2.17196461482771e-07    -6.91926313309958       downbta-miR-182     1882    33      84.318313       16.059043       0.00119553585103038     -3.81519649022355       downbta-miR-183     1544    40      69.175066       19.465506       0.00778797871791981     -3.25606929861198       downbta-miR-187     0       18      0       8.759478        6.10013036195234e-07    5.24714335099614        upbta-miR-196a    2871    31      128.627989      15.085767       0.000103494675187443    -4.51281538763237       down

bta.mir2target.list格式如下：

bta-let-7a-3p   EAS0021476;EAS0000070;EAS0013638;EAS0001074;EAS0004577;EAS0006787;EAS0008899;EAS0013962;EAS0017655;EAS0005413;EAS0006009bta-let-7a-5p   EAS0008419;EAS0003830;EAS0009803;EAS0011296;EAS0005793;EAS0004645;EAS0014772bta-let-7b      EAS0017817;EAS0013474;EAS0008780;EAS0018405;EAS0017359;EAS0017674;EAS0020797;EAS0015379;EAS0011272;EAS0010435;EAS0013631bta-let-7c      EAS0006104;EAS0004549;EAS0003321;EAS0010481;EAS0021491;EAS0015994;EAS0001788;EAS0002956;EAS0007473;EAS0008880;EAS0007345;EAS0003066bta-let-7d      EAS0005004;EAS0009924;EAS0020635;EAS0002650;EAS0011574

最后生成的文件如下所示：

miRNA   Gene    log2Ratio_miR   log2Ratio_Genebta-let-7c      EAS0003321      -1.43072567351625       1.37874741391777bta-let-7c      EAS0007345      -1.43072567351625       1.11756970634256bta-let-7c      EAS0003066      -1.43072567351625       1.67994238012443bta-let-7c      EAS0017368      -1.43072567351625       3.05079253633835bta-let-7c      EAS0004422      -1.43072567351625       1.50329494091278bta-let-7c      EAS0003988      -1.43072567351625       1.18612566219656bta-let-7c      EAS0005608      -1.43072567351625       1.89027598062113bta-let-7c      EAS0012078      -1.43072567351625       3.50870147552217bta-let-7c      EAS0015105      -1.43072567351625       1.06781330535694bta-let-7c      EAS0020084      -1.43072567351625       1.10413933910007

有了输入文件，然后就可以作图了，作图脚本比较简单，用法：

Rscript correlation_analysis.R -i Correlation_analysis_input.txt -n Correlation_analysis

脚本代码：

library(ggplot2)library('getopt');spec = matrix(c('help' , 'h', 0, "logical","for help",'input' , 'i', 1, "character","input file ,required",'name' , 'n', 1, "character","photo name"), byrow=TRUE, ncol=5);opt = getopt(spec);print_usage <- function(spec=NULL){cat(getopt(spec, usage=TRUE));q(status=1);}if ( !is.null(opt$help) ) { print_usage(spec) }if ( is.null(opt$input) ){ print_usage(spec) }if ( is.null(opt$name) ){ opt$name = "Correlation analysis" }point <- read.table(opt$input,sep="\t",header = TRUE,comment.char = "")p <- ggplot(point, aes(x=log2Ratio_miR, y=log2Ratio_Gene)) + geom_point(size=0.01,colour="red")+theme(######取消默认的背景颜色方框等panel.background = element_rect(fill = "transparent",colour = "black"), panel.grid.minor = element_blank(), panel.grid.major = element_blank(),plot.background = element_rect(fill = "transparent",colour = "black"))#输出文件名称png_name=paste(opt$name, ".png", sep="")pdf_name=paste(opt$name, ".pdf", sep="")#输出pdf格式图片pdf(pdf_name,width =3,height = 3)print(p)dev.off()#输出png格式图片png(png_name,width =2000,height =2000,res = 500,units = "px")print(p)dev.off()

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