powsimR
Version 1.2.4
powsimR
还请咨询我用PKGDOWN制作的Powsimr的Github页面！
对于安装，需要R包devtools 。
install.packages( " devtools " )
library( devtools )我建议先手动安装依赖项，然后再安装powsimr。如果您打算使用魔术进行插补，请在安装Powsimr之前按照他们的指示安装Python实现。
ipak <- function ( pkg , repository = c( " CRAN " , " Bioconductor " , " github " )) {
new.pkg <- pkg [ ! ( pkg %in% installed.packages()[, " Package " ])]
# new.pkg <- pkg
if (length( new.pkg )) {
if ( repository == " CRAN " ) {
install.packages( new.pkg , dependencies = TRUE )
}
if ( repository == " Bioconductor " ) {
if (strsplit( version [[ " version.string " ]], " " )[[ 1 ]][ 3 ] > " 4.0.0 " ) {
if ( ! requireNamespace( " BiocManager " )) {
install.packages( " BiocManager " )
}
BiocManager :: install( new.pkg , dependencies = TRUE , ask = FALSE )
}
if (strsplit( version [[ " version.string " ]], " " )[[ 1 ]][ 3 ] < " 3.6.0 " ) {
stop(message( " powsimR depends on packages and functions that are only available in R 4.0.0 and higher. " ))
}
}
if ( repository == " github " ) {
devtools :: install_github( new.pkg , build_vignettes = FALSE , force = FALSE ,
dependencies = TRUE )
}
}
}
# CRAN PACKAGES
cranpackages <- c( " broom " , " cobs " , " cowplot " , " data.table " , " doParallel " , " dplyr " ,
" DrImpute " , " fastICA " , " fitdistrplus " , " foreach " , " future " , " gamlss.dist " , " ggplot2 " ,
" ggpubr " , " ggstance " , " grDevices " , " grid " , " Hmisc " , " kernlab " , " MASS " , " magrittr " ,
" MBESS " , " Matrix " , " matrixStats " , " mclust " , " methods " , " minpack.lm " , " moments " ,
" msir " , " NBPSeq " , " nonnest2 " , " parallel " , " penalized " , " plyr " , " pscl " , " reshape2 " ,
" Rmagic " , " rsvd " , " Rtsne " , " scales " , " Seurat " , " snow " , " sctransform " , " stats " ,
" tibble " , " tidyr " , " truncnorm " , " VGAM " , " ZIM " , " zoo " )
ipak( cranpackages , repository = " CRAN " )
# BIOCONDUCTOR
biocpackages <- c( " bayNorm " , " baySeq " , " BiocGenerics " , " BiocParallel " , " DESeq2 " ,
" EBSeq " , " edgeR " , " IHW " , " iCOBRA " , " limma " , " Linnorm " , " MAST " , " monocle " , " NOISeq " ,
" qvalue " , " ROTS " , " RUVSeq " , " S4Vectors " , " scater " , " scDD " , " scde " , " scone " , " scran " ,
" SCnorm " , " SingleCellExperiment " , " SummarizedExperiment " , " zinbwave " )
ipak( biocpackages , repository = " Bioconductor " )
# GITHUB
githubpackages <- c( " cz-ye/DECENT " , " nghiavtr/BPSC " , " mohuangx/SAVER " , " statOmics/zingeR " ,
" Vivianstats/scImpute " )
ipak( githubpackages , repository = " github " )要检查是否安装了所有依赖项，您可以运行以下行：
powsimRdeps <- data.frame ( Package = c( cranpackages ,
biocpackages ,
sapply(strsplit( githubpackages , " / " ), " [[ " , 2 )),
stringsAsFactors = F )
ip <- as.data.frame(installed.packages()[,c( 1 , 3 : 4 )], stringsAsFactors = F )
ip.check <- cbind( powsimRdeps ,
Version = ip [match( powsimRdeps $ Package , rownames( ip )), " Version " ])
table(is.na( ip.check $ Version )) # all should be FALSE安装依赖项后，也可以使用DevTools安装POWSIMR。
devtools :: install_github( " bvieth/powsimR " , build_vignettes = TRUE , dependencies = FALSE )
library( " powsimR " )替代方案，您可以尝试使用DevTools直接安装Powsimr及其依赖项：
devtools :: install_github( " bvieth/powsimR " )有关使用包装的示例和提示，请在成功安装后咨询小插图
browseVignettes( " powsimR " )一些用户由于Vignette编译错误而在安装POWSIMR方面遇到了问题，或者因为他们缺少构建小插图的必要R软件包，即Knitr和rmdformats。如果是这种情况，您可以安装这些依赖项或忽略构建小插图（通过将build_vignettes设置为false），然后在我的powsimr的Github页面上读取它，或在此处将其作为HTML文件下载。
请注意，由于生物导体软件包加载了许多共享对象，可能会出现“达到DLL的最大数量……达到的最大数量……”。安装依赖项 / powsimr后重新启动R会话将有所帮助。从R版本3.4.0开始，可以将环境变量“ R_MAX_NUM_DLLS”设置为更高的数字。有关更多信息，请参见?Startup() 。我建议将可以加载到500的DLL的最大数量增加到500。环境变量r_max_num_dll可以在启动R_HOME/etc/renviron中设置R_HOME/ETC/RENVIROR。在启动R。为此，请添加以下行：r_max_num_dlls = xy where xy where xy是xy where xy white xy是XY dlls的数量。在我的Ubuntu机器上，Renviron文件在/usr/lib/r/etc/中，我可以将其设置为500。
此外，可能必须将开放文件的用户限制设置为更高的数字，以适应DLL的增加。请查看Mac和Linux的帮助页面以获取指导。
请使用以下条目引用powsimr。
citation( " powsimR " )Powsimr发表在生物信息学上。预印本纸也在生物氧化纸上。
请通过在此页面上打开新问题来发送错误报告和功能请求。我尝试了解POWSIMR中实现的新开发 /更改的最新信息，但是如果您在使用某个工具时遇到运行错误（例如，用于插补），那么我感谢您是否可以将其作为问题发布。
R会话信息library( powsimR )
# > Loading required package: gamlss.dist
# > Loading required package: MASS
# > Registered S3 method overwritten by 'gdata':
# > method from
# > reorder.factor gplots
# > Warning: replacing previous import 'DECENT::lrTest' by 'MAST::lrTest' when
# > loading 'powsimR'
# > Warning: replacing previous import 'penalized::predict' by 'stats::predict' when
# > loading 'powsimR'
# > Warning: replacing previous import 'zinbwave::glmWeightedF' by
# > 'zingeR::glmWeightedF' when loading 'powsimR'
sessionInfo()
# > R version 4.1.2 (2021-11-01)
# > Platform: x86_64-pc-linux-gnu (64-bit)
# > Running under: Ubuntu 18.04.6 LTS
# >
# > Matrix products: default
# > BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
# > LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
# >
# > locale:
# > [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
# > [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=en_US.UTF-8
# > [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=en_US.UTF-8
# > [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C
# > [9] LC_ADDRESS=C LC_TELEPHONE=C
# > [11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C
# >
# > attached base packages:
# > [1] stats graphics grDevices utils datasets methods base
# >
# > other attached packages:
# > [1] powsimR_1.2.3 gamlss.dist_6.0-1 MASS_7.3-54
# >
# > loaded via a namespace (and not attached):
# > [1] mixtools_1.2.0 softImpute_1.4-1
# > [3] minpack.lm_1.2-1 lattice_0.20-45
# > [5] vctrs_0.3.8 fastICA_1.2-3
# > [7] mgcv_1.8-38 penalized_0.9-51
# > [9] blob_1.2.2 survival_3.2-13
# > [11] prodlim_2019.11.13 Rmagic_2.0.3
# > [13] later_1.3.0 nloptr_1.2.2.3
# > [15] DBI_1.1.1 R.utils_2.11.0
# > [17] rappdirs_0.3.3 SingleCellExperiment_1.16.0
# > [19] Linnorm_2.18.0 dqrng_0.3.0
# > [21] jpeg_0.1-9 zlibbioc_1.40.0
# > [23] MatrixModels_0.5-0 htmlwidgets_1.5.4
# > [25] mvtnorm_1.1-3 future_1.23.0
# > [27] UpSetR_1.4.0 parallel_4.1.2
# > [29] scater_1.22.0 irlba_2.3.3
# > [31] DEoptimR_1.0-9 Rcpp_1.0.7
# > [33] KernSmooth_2.23-20 DT_0.20
# > [35] promises_1.2.0.1 gdata_2.18.0
# > [37] DDRTree_0.1.5 DelayedArray_0.20.0
# > [39] limma_3.50.0 vegan_2.5-7
# > [41] Hmisc_4.6-0 ShortRead_1.52.0
# > [43] apcluster_1.4.8 RSpectra_0.16-0
# > [45] msir_1.3.3 mnormt_2.0.2
# > [47] digest_0.6.28 png_0.1-7
# > [49] bluster_1.4.0 qlcMatrix_0.9.7
# > [51] sctransform_0.3.2 cowplot_1.1.1
# > [53] pkgconfig_2.0.3 docopt_0.7.1
# > [55] DelayedMatrixStats_1.16.0 gower_0.2.2
# > [57] ggbeeswarm_0.6.0 iterators_1.0.13
# > [59] minqa_1.2.4 lavaan_0.6-9
# > [61] reticulate_1.22 SummarizedExperiment_1.24.0
# > [63] spam_2.7-0 beeswarm_0.4.0
# > [65] modeltools_0.2-23 xfun_0.28
# > [67] zoo_1.8-9 tidyselect_1.1.1
# > [69] ZIM_1.1.0 reshape2_1.4.4
# > [71] purrr_0.3.4 kernlab_0.9-29
# > [73] EDASeq_2.28.0 viridisLite_0.4.0
# > [75] snow_0.4-4 rtracklayer_1.54.0
# > [77] rlang_0.4.12 hexbin_1.28.2
# > [79] glue_1.5.0 RColorBrewer_1.1-2
# > [81] fpc_2.2-9 matrixStats_0.61.0
# > [83] MatrixGenerics_1.6.0 stringr_1.4.0
# > [85] lava_1.6.10 fields_13.3
# > [87] ggsignif_0.6.3 DESeq2_1.34.0
# > [89] recipes_0.1.17 SparseM_1.81
# > [91] httpuv_1.6.3 class_7.3-19
# > [93] BPSC_0.99.2 BiocNeighbors_1.12.0
# > [95] annotate_1.72.0 jsonlite_1.7.2
# > [97] XVector_0.34.0 tmvnsim_1.0-2
# > [99] bit_4.0.4 mime_0.12
# > [101] gridExtra_2.3 gplots_3.1.1
# > [103] Rsamtools_2.10.0 zingeR_0.1.0
# > [105] stringi_1.7.5 gmodels_2.18.1
# > [107] rhdf5filters_1.6.0 bitops_1.0-7
# > [109] maps_3.4.0 RSQLite_2.2.8
# > [111] tidyr_1.1.4 pheatmap_1.0.12
# > [113] data.table_1.14.2 rstudioapi_0.13
# > [115] GenomicAlignments_1.30.0 nlme_3.1-153
# > [117] qvalue_2.26.0 scran_1.22.1
# > [119] fastcluster_1.2.3 locfit_1.5-9.4
# > [121] scone_1.18.0 listenv_0.8.0
# > [123] cobs_1.3-4 R.oo_1.24.0
# > [125] prabclus_2.3-2 segmented_1.3-4
# > [127] dbplyr_2.1.1 BiocGenerics_0.40.0
# > [129] lifecycle_1.0.1 timeDate_3043.102
# > [131] ROTS_1.22.0 munsell_0.5.0
# > [133] hwriter_1.3.2 R.methodsS3_1.8.1
# > [135] moments_0.14 caTools_1.18.2
# > [137] codetools_0.2-18 coda_0.19-4
# > [139] Biobase_2.54.0 GenomeInfoDb_1.30.0
# > [141] vipor_0.4.5 htmlTable_2.3.0
# > [143] bayNorm_1.12.0 rARPACK_0.11-0
# > [145] xtable_1.8-4 SAVER_1.1.2
# > [147] ROCR_1.0-11 diptest_0.76-0
# > [149] formatR_1.11 lpsymphony_1.22.0
# > [151] abind_1.4-5 FNN_1.1.3
# > [153] parallelly_1.29.0 RANN_2.6.1
# > [155] sparsesvd_0.2 CompQuadForm_1.4.3
# > [157] BiocIO_1.4.0 GenomicRanges_1.46.1
# > [159] tibble_3.1.6 ggdendro_0.1.22
# > [161] cluster_2.1.2 future.apply_1.8.1
# > [163] Matrix_1.3-4 ellipsis_0.3.2
# > [165] prettyunits_1.1.1 shinyBS_0.61
# > [167] lubridate_1.8.0 NOISeq_2.38.0
# > [169] shinydashboard_0.7.2 mclust_5.4.8
# > [171] igraph_1.2.9 ggstance_0.3.5
# > [173] slam_0.1-49 testthat_3.1.0
# > [175] doSNOW_1.0.19 htmltools_0.5.2
# > [177] BiocFileCache_2.2.0 GenomicFeatures_1.46.1
# > [179] yaml_2.2.1 utf8_1.2.2
# > [181] XML_3.99-0.8 ModelMetrics_1.2.2.2
# > [183] ggpubr_0.4.0 DrImpute_1.0
# > [185] foreign_0.8-81 withr_2.4.2
# > [187] scuttle_1.4.0 fitdistrplus_1.1-6
# > [189] BiocParallel_1.28.2 aroma.light_3.24.0
# > [191] bit64_4.0.5 foreach_1.5.1
# > [193] robustbase_0.93-9 outliers_0.14
# > [195] Biostrings_2.62.0 combinat_0.0-8
# > [197] rsvd_1.0.5 ScaledMatrix_1.2.0
# > [199] iCOBRA_1.22.1 memoise_2.0.1
# > [201] evaluate_0.14 VGAM_1.1-5
# > [203] nonnest2_0.5-5 geneplotter_1.72.0
# > [205] permute_0.9-5 caret_6.0-90
# > [207] curl_4.3.2 fdrtool_1.2.17
# > [209] fansi_0.5.0 conquer_1.2.1
# > [211] edgeR_3.36.0 checkmate_2.0.0
# > [213] cachem_1.0.6 truncnorm_1.0-8
# > [215] tensorA_0.36.2 DECENT_1.1.0
# > [217] ellipse_0.4.2 rjson_0.2.20
# > [219] metapod_1.2.0 ggplot2_3.3.5
# > [221] rstatix_0.7.0 ggrepel_0.9.1
# > [223] scDD_1.18.0 tools_4.1.2
# > [225] sandwich_3.0-1 magrittr_2.0.1
# > [227] RCurl_1.98-1.5 car_3.0-12
# > [229] pbivnorm_0.6.0 bayesm_3.1-4
# > [231] xml2_1.3.2 EBSeq_1.34.0
# > [233] httr_1.4.2 assertthat_0.2.1
# > [235] rmarkdown_2.11 Rhdf5lib_1.16.0
# > [237] boot_1.3-28 globals_0.14.0
# > [239] R6_2.5.1 nnet_7.3-16
# > [241] progress_1.2.2 genefilter_1.76.0
# > [243] KEGGREST_1.34.0 gtools_3.9.2
# > [245] statmod_1.4.36 beachmat_2.10.0
# > [247] BiocSingular_1.10.0 rhdf5_2.38.0
# > [249] splines_4.1.2 carData_3.0-4
# > [251] colorspace_2.0-2 amap_0.8-18
# > [253] generics_0.1.1 stats4_4.1.2
# > [255] NBPSeq_0.3.0 compositions_2.0-2
# > [257] base64enc_0.1-3 baySeq_2.28.0
# > [259] pillar_1.6.4 HSMMSingleCell_1.14.0
# > [261] GenomeInfoDbData_1.2.7 plyr_1.8.6
# > [263] dotCall64_1.0-1 gtable_0.3.0
# > [265] SCnorm_1.16.0 monocle_2.22.0
# > [267] restfulr_0.0.13 knitr_1.36
# > [269] RcppArmadillo_0.10.7.3.0 latticeExtra_0.6-29
# > [271] biomaRt_2.50.1 IRanges_2.28.0
# > [273] fastmap_1.1.0 doParallel_1.0.16
# > [275] pscl_1.5.5 flexmix_2.3-17
# > [277] quantreg_5.86 AnnotationDbi_1.56.2
# > [279] broom_0.7.10 filelock_1.0.2
# > [281] scales_1.1.1 arm_1.12-2
# > [283] backports_1.4.0 plotrix_3.8-2
# > [285] IHW_1.22.0 S4Vectors_0.32.3
# > [287] densityClust_0.3 ipred_0.9-12
# > [289] lme4_1.1-27.1 hms_1.1.1
# > [291] Rtsne_0.15 dplyr_1.0.7
# > [293] shiny_1.7.1 grid_4.1.2
# > [295] Formula_1.2-4 blockmodeling_1.0.5
# > [297] crayon_1.4.2 MAST_1.20.0
# > [299] RUVSeq_1.28.0 pROC_1.18.0
# > [301] sparseMatrixStats_1.6.0 viridis_0.6.2
# > [303] rpart_4.1-15 zinbwave_1.16.0
# > [305] compiler_4.1.2
