R语言的exp_immu_cor_plot.r如何使用
这篇“R语言的exp_immu_cor_plot.r如何使用”文章的知识点大部分人都不太理解,所以小编给大家总结了以下内容,内容详细,步骤清晰,具有一定的借鉴价值,希望大家阅读完这篇文章能有所收获,下面我们一起来看看这篇“R语言的exp_immu_cor_plot.r如何使用”文章吧。
exp_immu_cor_plot.r 基因表达量与免疫侵润相关性绘图分析
使用方法:
$Rscript ../scripts/exp_immu_cor_plot.r -h usage: ../scripts/exp_immu_cor_plot.r [-h] -e expset -i immu [-m method] [-a alternative] [-n ncol] [-l] [-x label.x.npc] [-y label.y.npc] [-o outdir] [-H height] [-W width] scattor correlateion plot: https://www.蜗牛博客.com/article/1488 optional arguments: -h, --help show this help message and exit -e expset, --expset expset set event column name [required] -i immu, --immu immu input data file path[required] -m method, --method method a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson", "kendall", or "spearman". [default pearson] -a alternative, --alternative alternative a character string specifying the alternative hypothesis, must be one of "two.sided" , "greater" or "less". You can specify just the initial letter. [default two.sided] -n ncol, --ncol ncol column num [default [default 4] -l, --log2 Whether to do log2 transformation of gene expression [default FALSE] -x label.x.npc, --label.x.npc label.x.npc value should be between 0 and 1. Coordinates to be used for positioning the label, expressed in "normalized parent coordinates". [default 0] -y label.y.npc, --label.y.npc label.y.npc value should be between 0 and 1. Coordinates to be used for positioning the label, expressed in "normalized parent coordinates". [default 1] -o outdir, --outdir outdir output file directory [default cwd] -H height, --height height the height of pic inches [default 5] -W width, --width width the width of pic inches [default 10]
使用举例:
Rscript ../scripts/exp_immu_cor_plot.r -e gene_exp1.tsv -i ../03.TIME/immu/timer.res.tsv -o timer_cor1 --log2
参数说明:
-e 指定输入指定基因的表达量,行为 基因,列为样本名称
ID | TCGA-D7-A74A-01A-11R-A32D-31 | TCGA-BR-7704-01A-11R-2055-13 | TCGA-VQ-A91N-01A-11R-A414-31 | TCGA-CD-A4MH-01A-11R-A251-31 |
NUP50 | 18.65505 | 31.59232 | 28.23382 | 28.76485 |
CXCR4 | 64.85805 | 125.123 | 56.35244 | 69.98976 |
NT5E | 111.4818 | 69.8587 | 79.37382 | 25.05824 |
EFNA3 | 8.247857 | 42.03308 | 43.46432 | 26.66024 |
STC1 | 4.781111 | 21.36327 | 40.81077 | 19.51568 |
ZBTB7A | 95.51678 | 103.4768 | 158.3024 | 126.2677 |
CLDN9 | 1.187456 | 2.476138 | 0.366081 | 7.347344 |
-i 输入样本免疫侵润结果, 注意脚本会自动对两个文件里的样本取交集
cell_type | TCGA-B7-A5TK-01A-12R-A36D-31 | TCGA-BR-7959-01A-11R-2343-13 | TCGA-IN-8462-01A-11R-2343-13 | TCGA-BR-A4CR-01A-11R-A24K-31 |
B cell | 0 | 0.013159742 | 0.000907507 | 0.020234 |
T cell CD4+ | 0 | 0.114882797 | 0.118061151 | 0.152274 |
T cell CD8+ | 0.771121767 | 0.130798349 | 0.048964712 | 0.005392 |
Neutrophil | 0.22692792 | 0.125194736 | 0.106562343 | 0.057013 |
Macrophage | 0 | 0.213365358 | 0 | 0.05444 |
Myeloid dendritic cell | 0.935644191 | 0.457844399 | 0.404774813 | 0.296719 |
以上就是关于“R语言的exp_immu_cor_plot.r如何使用”这篇文章的内容,相信大家都有了一定的了解,希望小编分享的内容对大家有帮助,若想了解更多相关的知识内容,请关注蜗牛博客行业资讯频道。
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:niceseo99@gmail.com进行举报,并提供相关证据,一经查实,将立刻删除涉嫌侵权内容。版权声明:如无特殊标注,文章均为本站原创,转载时请以链接形式注明文章出处。
评论