这篇“R语言的edger_analysis.r怎么用”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edger_analysis.r怎么用”文章吧。
edger_analysis.r 差异基因分析edgeR
使用方法:
$Rscript $scriptdir/edger_analysis.r -h usage: /work/my_stad_immu/scripts/edger_analysis.r [-h] -i filepath -m filepath -t treatname --control CONTROL --case CASE [-f fdr] [-c fc] [-s size] [-a alpha] [-X x.lab] [-Y y.lab] [-T title] [-H height] [-W width] [-o path] [-p prefix] edgeR analysis : https://www.亿速云.com/article/1506 optional arguments: -h, --help show this help message and exit -i filepath, --input filepath input read count file [required] -m filepath, --metadata filepath metadata file , required -t treatname, --treatname treatname treat colname in group file, required --control CONTROL set control group name required --case CASE set case group name required -f fdr, --fdr fdr set fdr threshold [default 0.05] -c fc, --fc fc set fold change threshold [default 2] -s size, --size size point size [optional, default: 0.7] -a alpha, --alpha alpha point transparency [0-1] [optional, default: 1] -X x.lab, --x.lab x.lab the label for x axis [optional, default: log2FC] -Y y.lab, --y.lab y.lab the label for y axis [optional, default: -log10(FDR)] -T title, --title title the label for main title [optional, default: Volcano] -H height, --height height the height of pic inches [default 5] -W width, --width width the width of pic inches [default 5] -o path, --outdir path output file directory [default /work/my_stad_immu/05.enrich] -p prefix, --prefix prefix out file name prefix [default Volcano]
参数说明:
-i 输入基因表达矩阵文件,必须为count表达文件:
ID | 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 | TCGA-CG-4443-01A-01R-1157-13 | TCGA-KB-A93J-01A-11R-A39E-31 | TCGA-BR-4371-01A-01R-1157-13 |
TSPAN6 | 5951 | 4036 | 2834 | 3484 | 2537 | 2027 | 4749 |
TNMD | 3 | 4 | 0 | 1 | 0 | 1 | 8 |
DPM1 | 4672 | 4330 | 1725 | 4370 | 6523 | 3094 | 4415 |
SCYL3 | 1260 | 2057 | 702 | 1483 | 924 | 1451 | 982 |
C1orf112 | 523 | 992 | 172 | 1400 | 234 | 733 | 958 |
FGR | 1249 | 1127 | 285 | 148 | 56 | 941 | 208 |
CFH | 12831 | 11435 | 5387 | 995 | 4571 | 2189 | 1795 |
FUCA2 | 5896 | 7857 | 3208 | 5625 | 1527 | 7530 | 3290 |
GCLC | 2682 | 5509 | 1447 | 9323 | 6422 | 5265 | 2418 |
-m metadata文件路径,样本的分组信息,第一列必须和表达文件的样本名称对应:
barcode | subtype.hclust | StromalScore | ImmuneScore | ESTIMATEScore | TumourPurity |
TCGA-B7-A5TK-01A-12R-A36D-31 | S1 | 1026.057 | 2386.835 | 3412.892 | 0.448276 |
TCGA-BR-7959-01A-11R-2343-13 | S2 | 1130.722 | 729.402 | 1860.124 | 0.638667 |
TCGA-IN-8462-01A-11R-2343-13 | S2 | 112.2318 | 683.9349 | 796.1667 | 0.750581 |
TCGA-BR-A4CR-01A-11R-A24K-31 | S2 | -1060.35 | -766.618 | -1826.97 | 0.943814 |
TCGA-CG-4443-01A-01R-1157-13 | S2 | -261.577 | -258.629 | -520.206 | 0.8635 |
TCGA-KB-A93J-01A-11R-A39E-31 | S1 | -202.255 | 1605.12 | 1402.865 | 0.688838 |
TCGA-BR-4371-01A-01R-1157-13 | S2 | -828.231 | 711.3379 | -116.893 | 0.832147 |
TCGA-IN-A6RO-01A-12R-A33Y-31 | S2 | -1406.57 | 68.58307 | -1337.98 | 0.917683 |
TCGA-HU-A4H3-01A-21R-A251-31 | S2 | -619.208 | 538.7225 | -80.4854 | 0.829171 |
TCGA-RD-A8MV-01A-11R-A36D-31 | S1 | 113.4127 | 2309.647 | 2423.06 | 0.572976 |
TCGA-VQ-A91X-01A-12R-A414-31 | S2 | -1845.85 | -590.017 | -2435.87 | 0.969545 |
TCGA-D7-8575-01A-11R-2343-13 | S2 | -206.112 | 1392.799 | 1186.687 | 0.711491 |
TCGA-BR-4257-01A-01R-1131-13 | S1 | 861.029 | 1676.148 | 2537.177 | 0.559167 |
TCGA-BR-8485-01A-11R-2402-13 | S1 | 373.0961 | 1110.516 | 1483.612 | 0.680198 |
TCGA-BR-4370-01A-01R-1157-13 | S1 | 1300.495 | 1802.327 | 3102.822 | 0.488483 |
-t subtype.hclust –case S1 –control S2 : 指定metadata 分组列名,分组里面的比较组名字 ,如果分组名字有空格,应该用引号引起来: “Stage IA”
–fdr 0.01 –fc 2 设置差异基因的筛选条件: 显著性和差异倍数
使用举例:
Rscript $scriptdir/edger_analysis.r -i ../01.TCGA_download/TCGA-STAD_gene_expression_Counts.tsv \ --fdr 0.01 --fc 2 \ -m ../03.TIME/metadata.group.tsv -t subtype.hclust --case S1 --control S2 -p S1_vs_S2