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R语言的hclust_analysis.r如何使用

发表于:2025-02-01 作者:千家信息网编辑
千家信息网最后更新 2025年02月01日,本篇内容介绍了"R语言的hclust_analysis.r如何使用"的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能
千家信息网最后更新 2025年02月01日R语言的hclust_analysis.r如何使用

本篇内容介绍了"R语言的hclust_analysis.r如何使用"的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能够学有所成!

hclust_analysis.r 转录组数据层次聚类分析

使用说明:

usage: hclust_analysis.r [-h] -i filepath [-d distance] [-m method] [-T top]                         [-S] [-M max.nc] [-k bestk] [-s size] [-a alpha] [-e]                         [-L] [-X label] [-Y label] [-t label] [-o path]                         [-H number] [-W number]Hierarchical Clustering andplot:https://clincancerres.aacrjournals.org/content/25/16/5002optional arguments:  -h, --help            show this help message and exit  -i filepath, --input filepath                        input the dataset martix [required]  -d distance, --distance distance                        the distance measure to be used to compute the                        dissimilarity matrix. This must be one of:                        "euclidean", "maximum", "manhattan", "canberra",                        "binary", "minkowski" . By default,                        distance="euclidean".  -m method, --method method                        the cluster analysis method to be used. This should be                        one of: "ward.D", "ward.D2", "single", "complete",                        "average", "mcquitty", "median", "centroid". by                        default method=ward.D  -T top, --top top     select top gene to analysis [default NULL]  -S, --scale           scale data sd=1 mean=0 [default FALSE]  -M max.nc, --max.nc max.nc                        maximal number of clusters for nbclust, between 2 and                        (number of objects - 1), greater or equal to min.nc.                        By default [optional, default: 15]  -k bestk, --bestk bestk                        set bestk or nbclust choose bestk [optional, default:                        NULL]  -X label, --x.lab label                        the label for x axis [optional, default: sample ]  -Y label, --y.lab label                        the label for y axis [optional, default: Distance ]  -t label, --title label                        the label for main title [optional, default: Cluster                        Dendrogram]  -o path, --outdir path                        output file directory [default cwd]  -H number, --height number                        the height of pic inches [default 5]  -W number, --width number                        the width of pic inches [default 10]

使用方法:

应该运行两次

#第一次运行不指定K,通过nbclust 结果选择合适的K (亚型)Rscript $scriptdir/hclust_analysis.r -i immu/ssgsea.res.tsv  -o hclust  -M 20 --distance "euclidean"  #再次运行指定最佳K,输出聚类树和分组表格Rscript $scriptdir/hclust_analysis.r -i immu/ssgsea.res.tsv  -o hclust   --distance "euclidean" -k 2

参数说明:

-i 输入基因表达矩阵文件,或者免疫侵润矩阵文件

cell_typeTCGA-B7-A5TK-01A-12R-A36D-31TCGA-BR-7959-01A-11R-2343-13TCGA-IN-8462-01A-11R-2343-13TCGA-BR-A4CR-01A-11R-A24K-31TCGA-CG-4443-01A-01R-1157-13
aDC0.6121310.4527210.4340650.3526350.268974
B cells0.4233230.408870.4266120.4138570.289268
Blood vessels0.6810230.7754390.6894330.5776670.745019
CD8 T cells0.6756150.6500730.6291210.5660480.577315
Cytotoxic cells0.6210560.4252170.4116170.31280.191034
DC0.6198390.4850560.4891010.2669050.350132
Eosinophils0.5027850.5149390.4695410.4880510.456521
iDC0.531620.4984370.5309310.3906990.420172
Lymph vessels0.7108430.7213230.6583910.5005740.400411
Macrophages0.6082710.5984820.5522770.4685310.438481
Mast cells0.4807920.5259270.478710.246770.124795
Neutrophils0.4476720.4580980.3935410.31050.344511
NK CD56bright cells0.4626330.4186170.5460940.572620.460983
NK CD56dim cells0.3414740.1371470.031158-0.04299-0.0389
NK cells0.5581230.5129290.5070880.4795420.446198
Normal mucosa0.7794440.8202810.8067710.6913840.65646
pDC0.6767720.6474150.6211860.4825640.552156
SW480 cancer cells0.5341510.6002360.6185090.4121960.60535
T cells0.6270560.4254220.3996120.3261160.188205
T helper cells0.6691030.6454070.628070.6502160.628577
Tcm0.5624080.5599510.5272720.5160680.553444
Tem0.5189520.5559420.4105770.4400070.449251
TFH0.4851240.4777490.4450610.4655520.446549
Tgd0.1901990.1101390.0616480.0040260.023796
Th2 cells0.5639280.4917360.4555230.4263510.378701
Th27 cells0.4172750.1537130.2187270.2150260.257282
Th3 cells0.5361420.4786870.447160.5395340.416747
TReg0.6820360.4847610.5169630.308840.312123

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