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> protein_data_B30_min<-protein_data[1:2548,10:12] > protein_data_M30_min<-protein_data[1:2548,19:21] > protein_data_30_min<-data.frame(protein_data_B30_min,protein_data_M30_min) > protein_data_30_min[1:2,] B30 B30.1 B30.2 Mgo30 Mgo30.1 Mgo30.2 1 870.5042 867.0873 0 1086.82[......] […]
> install.packages('plotrix') Installing package(s) into ‘/home/shenzy/R/x86_64-pc-linux-gnu-library/2.15’ (as ‘lib’ is unspecified) 试开URL’http://cran.csiro.au/src/contrib/plotrix_3.4-5.tar.gz' Content type 'application/x-gzip' length 211113 bytes (206 Kb) 打开了URL ==================[......]
[…] Testing i.pca ~ prcomp(), m.eigensystem ~ princomp()1. Briefly about PCA 2. The modules/functions that implement PCA in GRASS & R 3. My claims (Entitled Comments) 4. Evidence (=the numbers derived from i.pca, prcomp, princomp, m.eigensystem using some MODIS surface reflectance bands).[……] […] ############################### PCA ############################### install.packages(“vegan”) library(vegan) > STpcoa<-read.table(file=”bactera_16s_final.subsample.phylip.tre1.weighted.phylip.pcoa.axes”, header=T,row.names=1) > STpcoa axis1 axis2 axis3 axis4 Cellulose -0.020878[……] […] Difference between prcomp and princomp: ‘princomp’ can only be used with more units than variables” prcomp是基于SVD分解（svd()函数，princomp是基于特征向量eigen()函数) Good video source: http://www.youtube.com/watch?v=oZ2nfIPdvjY http://www.youtube.com/watch?v=I5GxNzKLIoU&feature=relmfu http://ww[……] […] > gtsdata_test=read.table(“gtsdata.txt”, header=T) > gtsenv=read.table(“gtsenv.txt”, header=T) > gtsdata_data_t<-t(gtsdata_data) > decorana(gtsdata_data_t) Call: decorana(veg = gtsdata_data_t) Detrended correspondence analysis with 26 segments. Rescaling of axes w[……] […] a.str <- matrix(c(‘1′,’2′,’3′,’5′,NA,’6′) + ,c(2,3),dimnames = list(c(‘g1′,’g2′),c(‘t1′,’t2′,’t3′))) a.str # t1 t2 t3 # g1 “1” “3” NA # g2 “2” “5” “6” a.num <- apply(a.str, c(1,2), as.numeric) a.num # t1 t2 t3 # g1 1 3 NA # g2 2 5 6 Note: 第一行，第一列位置要为空！！ […] “基于Vegan 软件包的生态学数据排序分析 赖江山 米湘成 (中国科学院植物研究所植被与环境变化国家重点实验室，北京 100093) 摘要：群落学数据一般是多维数据，例如物种属性或环境因子的属性。多元统计分析是群落生态学常用的分析方法，排序（ordination）是多元统计最常用的方法之一。CANOCO是广泛使用的排序软件，但缺点是商业软件价格不菲，版本更新速度也很慢。近年来，R语言以其灵活、开放、易于掌握、免费等诸多优点，在生态学和生物多样性研究领域迅速赢得广大研究人员的青睐。R语言中的外在软件包“Vegan”是专门用于群落生态学分析的工具。Vegan能够提供所有基本的排序方法，同时[……] […] source(“http://www.bioconductor.org/biocLite.R”); biocLite(“affy”); biocLite(“Biobase”); library(affy); library(Biobase); >bac_4sampledata=read.csv(“/home/R_heatmap/4sample_R_cluster.csv”, sep=”\t”) > row.names(bac_4sampledata)<-bac_4sampledata$Group > bac_4sample_Datamatrix<[……] […] Glancing at the code for […] |
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