powsimR
Version 1.2.4
powsimR
يرجى أيضًا استشارة صفحة GitHub الخاصة بي من Powsimr المصنوعة من PKGDown!
للتثبيت ، هناك حاجة إلى devtools حزمة R.
install.packages( " devtools " )
library( devtools )أوصي بتثبيت التبعيات أولاً يدويًا ثم powsimr. إذا كنت تخطط لاستخدام السحر من أجل التضمين ، فيرجى اتباع تعليماتهم لتثبيت تطبيق Python قبل تثبيت Powsimr.
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 " )للتحقق مما إذا كانت جميع التبعيات مثبتة ، يمكنك تشغيل الأسطر التالية:
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 FALSEبعد تثبيت التبعيات ، يمكن تثبيت powsimr باستخدام DevTools أيضًا.
devtools :: install_github( " bvieth/powsimR " , build_vignettes = TRUE , dependencies = FALSE )
library( " powsimR " )بديل ، يمكنك محاولة تثبيت powsimr وتبعياته مباشرة باستخدام DevTools:
devtools :: install_github( " bvieth/powsimR " )للحصول على أمثلة ونصائح حول استخدام الحزمة ، يرجى الرجوع إلى VIGNETTE بعد التثبيت الناجح بواسطة
browseVignettes( " powsimR " )واجه بعض المستخدمين مشكلات في تثبيت powsimr بسبب أخطاء تجميع المقالة القصيرة أو لأنهم يفتقدون حزم r اللازمة لبناء المقالات القصيرة ، IE knitr و rmdformats. إذا كان هذا هو الحال ، فيمكنك إما تثبيت هذه التبعيات أو ترك بناء المقالة القصيرة (عن طريق تعيين Build_vignettes إلى False) وقراءتها على صفحة GitHub الخاصة بي من Powsimr أو تنزيلها كملف HTML هنا.
لاحظ أن الخطأ "العدد الأقصى للمواد التي تم الوصول إليها ..." قد يحدث بسبب تحميل العديد من الكائنات المشتركة بواسطة حزم الموصلات الحيوية. سيساعد إعادة تشغيل جلسة R بعد تثبيت التبعيات / powsimr. بدءًا من الإصدار R 3.4.0 ، يمكن للمرء تعيين المتغير البيئي "R_MAX_NUM_DLLS" على رقم أعلى. انظر ?Startup() لمزيد من المعلومات. أوصي بزيادة الحد الأقصى لعدد DLLs التي يمكن تحميلها إلى 500. يمكن تعيين المتغير البيئي R_MAX_NUM_NUM_DLLS في R_HOME/ETC/RENVIRIN قبل بدء R. لتحديد موقع ملف RENViron وإضافة السطر التالي: R_MAX_NUM_DLLS = XY حيث يكون XY هو رقم DLLs. على جهاز Ubuntu الخاص بي ، يكون ملف Renviron في/usr/lib/r/etc/يمكنني ضبطه على 500.
بالإضافة إلى ذلك ، قد يتعين ضبط حدود المستخدم للملفات المفتوحة (UNIX: ULIMIT) على رقم أعلى لاستيعاب الزيادة في DLLs. يرجى مراجعة صفحات المساعدة الخاصة بـ Macs و Linux للحصول على التوجيه.
يرجى استخدام الإدخال التالي للإشارة إلى powsimr.
citation( " powsimR " )يتم نشر powsimr في المعلوماتية الحيوية. ورقة preprint هي أيضا على biorxiv.
يرجى إرسال تقارير الأخطاء وطلبات الميزات عن طريق فتح مشكلة جديدة في هذه الصفحة. أحاول مواكبة التطورات / التغييرات الجديدة للطرق التي تم تنفيذها في Powsimr ، ولكن إذا واجهت أخطاء تشغيل أثناء استخدام أداة معينة (على سبيل المثال للتأمين) ، فأنا أقدر ما إذا كنت تستطيع نشر هذا كمشكلة.
R معلومات الجلسة 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
