内容

在mosbi包,biclusters相似性计算使用不同的相似性度量。

这个描述概述关于实现的指标。

库(mosbi)

下面的相似性度量目前实现:

# Bray-Curtis相似bray_curtis < -函数(s1, s2,重叠){返回(((2 *重叠)/ (s1 + s2)))} # Jaccard指数Jaccard < -函数(s1, s2,重叠){返回(((重叠)/ (s1 + s2 -重叠)))}#重叠系数重叠< -函数(s1, s2,重叠){返回((重叠/分钟(s1, s2)))} # Fowlkes-Mallows指数folkes_mallows < -函数(s1, s2,重叠){tp < -选择(重叠,2)fp < -选择(s1 -重叠,2)fn < -选择(s2 -重叠,2)返回(返回值((tp / (tp + fp)) * (tp / (tp + fn))))}

相似性度量的行为将评估两个场景:

#场景1 -两个相同大小的biclusters size1_1 < -代表(1000、1000)size2_1 <代表(1000、1000)overlap_1 < - seq(1000) #场景2 -两个biclusters一个大小为500,其他的大小1000 size1_2 < -代表(1000、500)size2_2 <代表(500、500)overlap_2 < - seq (500)

两个相同大小的biclusters:

情节(overlap_1 bray_curtis (size1_1, size2_1 overlap_1)坳=“红色”,类型=“l”, xlab =“重叠”,ylab =“相似性”,ylim = c(0,1))行(overlap_1, jaccard (size1_1, size2_1 overlap_1)坳=“蓝色”)行(overlap_1,重叠(size1_1, size2_1 overlap_1) =“绿色”,上校lty = 2)线(overlap_1, folkes_mallows (size1_1, size2_1 overlap_1)坳=“橙色”)传说(x = 8,传说= c (“Bray-Curtis”、“jaccard”,“重叠”,“Fowlkes-Mallows”),坳= c(“红”“蓝”,“绿色”、“橙色”),lty = 1, cex = 0.8, title =“相似性度量”)

两种不同尺寸的biclusters:

情节(overlap_2 bray_curtis (size1_2, size2_2 overlap_2)坳=“红色”,类型=“l”, xlab =“重叠”,ylab =“相似性”,ylim = c(0,1))行(overlap_2, jaccard (size1_2, size2_2 overlap_2)坳=“蓝色”)行(overlap_2,重叠(size1_2, size2_2 overlap_2)坳=“绿色”)行(overlap_2, folkes_mallows (size1_2, size2_2 overlap_2)坳=“橙色”)传说(x = 8,传说= c (“Bray-Curtis”、“jaccard”,“重叠”,“Fowlkes-Mallows”),坳= c(“红”“蓝”,“绿色”、“橙色”),lty = 1, cex = 0.8, title =“相似性度量”)

1会话信息

sessionInfo () # > R版本4.2.0 RC (2022-04-19 r82224) # >平台:x86_64-pc-linux-gnu(64位)# >下运行:Ubuntu 20.04.4 LTS # > # >矩阵产品:默认# >布拉斯特区:/home/biocbuild/bbs - 3.15 - bioc / R / lib / libRblas。所以# > LAPACK: /home/biocbuild/bbs - 3.15 - bioc / R / lib / libRlapack。所以# > # >语言环境:# > [1]LC_CTYPE = en_US。utf - 8 LC_NUMERIC c# = >[3]而= en_GB LC_COLLATE = c# > [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 # > # >附加基本包:# >[1]统计图形grDevices跑龙套数据集方法基础# > # >其他附加包:# > [1]mosbi_1.2.0 BiocStyle_2.24.0 # > # >加载通过名称空间(而不是附加):# > [1]tidyselect_1.1.2 modeltools_0.2-23 xfun_0.30 # > [4] bslib_0.3.1 purrr_0.3.4 lattice_0.20-45 # > [7] flexclust_1.4-1 generics_0.1.2 colorspace_2.0-3 # > [10] vctrs_0.4.1 htmltools_0.5.2 stats4_4.2.0 # > [13] yaml_2.3.5 utf8_1.2.2 rlang_1.0.2 # > [16] jquerylib_0.1.4 pillar_1.7.0 DBI_1.1.2 # > [19] glue_1.6.2 BiocGenerics_0.42.0 RColorBrewer_1.1-3 # > [22] QUBIC_1.24.0 lifecycle_1.0.1 stringr_1.4.0 # > [25] munsell_0.5.0 gtable_0.3.0 evaluate_0.15 # > [28] Biobase_2.56.0 knitr_1.38 fastmap_1.1.0 # > [31] parallel_4.2.0 class_7.3-20 fansi_1.0.3 # > [34] biclust_2.0.3 highr_0.9 Rcpp_1.0.8.3 # > [37] scales_1.2.0 BiocManager_1.30.17 additivityTests_1.1-4 # > [40] RcppParallel_5.1.5 magick_2.7.3 jsonlite_1.8.0 # > [43] fabia_2.42.0 ggplot2_3.3.5 digest_0.6.29 # > [46] stringi_1.7.6 dplyr_1.0.8 bookdown_0.26 # > [49] grid_4.2.0 BH_1.78.0-0 cli_3.3.0 # > [52] tools_4.2.0 magrittr_2.0.3 sass_0.4.1 # > [55] tibble_3.1.6 tidyr_1.2.0 pkgconfig_2.0.3 # > [58] crayon_1.5.1 isa2_0.3.5 MASS_7.3-57 # > [61] ellipsis_0.3.2 assertthat_0.2.1 rmarkdown_2.14 # > [64] R6_2.5.1 igraph_1.3.1 compiler_4.2.0