Visualization
Density
Hierarchical clustering
Heatmaps
Interactive motionchart
Histograms, Clusters
Project high-dimensional data on two-dimensional plane by various methods including PCA, MDS, Sammons mapping etc. (for visualization purposes; see help(project.data) for details):
library(microbiome, quietly = TRUE)
data.directory <- system.file("extdata", package = "microbiome")
genus.matrix.log10.simulated <- read.profiling(level = "L2", method = "frpa",
data.dir = data.directory, log10 = TRUE)
# Note: transpose the data matrix into samples x features
proj <- project.data(t(genus.matrix.log10.simulated), type = "MDS.nonmetric")## initial value 15.632295
## iter 5 value 12.895757
## iter 10 value 11.421017
## iter 15 value 11.072375
## iter 15 value 11.064577
## iter 20 value 10.139051
## iter 25 value 9.781502
## final value 9.705087
## converged
# Plot the projection
library(ggplot2);
theme_set(theme_bw(15))
ggplot(aes(x = Comp.1, y = Comp.2), data = proj) + geom_point()Plot the projection with sample names:
ggplot(aes(x = Comp.1, y = Comp.2, label = rownames(proj)), data = proj) + geom_text()Plot subject age versus phylotype abundance with smoothed confidence intervals:
library(microbiome)
N <- 250
df <- data.frame(age = sort(runif(N, 0, 100)), hitchip = rnorm(N))
p <- vwReg(hitchip~age, df, shade = TRUE, mweight = TRUE, verbose = FALSE)## Error in eval(expr, envir, enclos): could not find function "vwReg"
p <- p + xlab("Age (y)") + ylab("HITChip Signal") ## Error in p + xlab("Age (y)"): non-numeric argument to binary operator
print(p)## NULL
- theme_bottom_border: ggplot2 theme
sessionInfo()## R version 3.1.2 (2014-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] ggplot2_1.0.0 microbiome_0.99.38 AnnotationDbi_1.28.1
## [4] GenomeInfoDb_1.2.4 IRanges_2.0.1 S4Vectors_0.4.0
## [7] Biobase_2.26.0 BiocGenerics_0.12.1 RSQLite_1.0.0
## [10] DBI_0.3.1 reshape_0.8.5 vegan_2.2-1
## [13] lattice_0.20-30 permute_0.8-3 e1071_1.6-4
## [16] knitr_1.9
##
## loaded via a namespace (and not attached):
## [1] acepack_1.3-3.3 ade4_1.6-2 boot_1.3-15
## [4] class_7.3-12 cluster_2.0.1 codetools_0.2-11
## [7] colorspace_1.2-6 devtools_1.7.0 df2json_0.0.2
## [10] digest_0.6.8 doParallel_1.0.8 dynamicTreeCut_1.62
## [13] earlywarnings_1.1.19 evaluate_0.5.5 fastcluster_1.1.16
## [16] fields_8.2-1 foreach_1.4.2 foreign_0.8-63
## [19] formatR_1.0 Formula_1.2-0 GO.db_3.0.0
## [22] grid_3.1.2 gtable_0.1.2 Hmisc_3.15-0
## [25] igraph_0.7.1 impute_1.40.0 iterators_1.0.7
## [28] Kendall_2.2 KernSmooth_2.23-14 labeling_0.3
## [31] latticeExtra_0.6-26 lmtest_0.9-33 maps_2.3-9
## [34] maptree_1.4-7 MASS_7.3-39 Matrix_1.1-5
## [37] matrixStats_0.14.0 mgcv_1.8-5 mixOmics_5.0-3
## [40] moments_0.14 munsell_0.4.2 nlme_3.1-120
## [43] nnet_7.3-9 nortest_1.0-3 pheatmap_1.0.2
## [46] plyr_1.8.1 preprocessCore_1.28.0 proto_0.3-10
## [49] quadprog_1.5-5 RColorBrewer_1.1-2 Rcpp_0.11.5
## [52] reshape2_1.4.1 RGCCA_2.0 rgl_0.95.1201
## [55] rjson_0.2.15 rpart_4.1-9 scales_0.2.4
## [58] som_0.3-5 spam_1.0-1 splines_3.1.2
## [61] stringr_0.6.2 survival_2.38-1 tgp_2.4-11
## [64] tools_3.1.2 tseries_0.10-34 WGCNA_1.43
## [67] zoo_1.7-11