zkl

  • 2023年5月3日
  • 注册于 2023年1月10日
  • 问题描述:

    因为我的数据每个时间点有多个重复样本,所以我想要使用circacompare包中的circacompare_mixed()比较两组(对照组和实验组)基因表达量的节律特征,并且基因数量达5000多个(这里只摘取了其中两个),因此我又用了for循环,但跑不出结果且出现了报错和警示:Iteration 1, LME step: nlminb() did not converge (code = 1). Do increase 'msMaxIter'!Error in nlme.formula(model = form_group, random = randomeffects_formula, :
    Unable to form Cholesky decomposition: the leading minor of order 1 is not pos.def.

    我的数据:

    dput(t)
    structure(list(id = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 
    3, 3, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3), group = c("CON", 
    "CON", "CON", "CON", "CON", "CON", "CON", "CON", "CON", "CON", 
    "CON", "CON", "CON", "CON", "CON", "CC", "CC", "CC", "CC", "CC", 
    "CC", "CC", "CC", "CC", "CC", "CC", "CC", "CC", "CC", "CC"), 
        time = c(0, 6, 12, 18, 24, 0, 6, 12, 18, 24, 0, 6, 12, 18, 
        24, 0, 6, 12, 18, 24, 0, 6, 12, 18, 24, 0, 6, 12, 18, 24), 
        Gnai3 = c(17.51364, 17.0441, 20.73355, 16.02792, 9.2444, 
        20.62992, 17.28127, 29.32941, 14.5062, 16.66473, 8.196866, 
        8.362214, 39.94942, 16.29845, 19.80216, 13.74092, 14.08834, 
        14.04772, 26.00864, 17.1612, 14.19446, 12.62367, 13.53981, 
        43.95303, 18.80314, 15.35234, 16.63615, 23.49265, 39.86695, 
        16.80003), Scmh1 = c(1.151244, 1.007064, 0.8978803, 0.8906483, 
        1.073716, 1.133559, 0.9923863, 0.3706273, 0.9956849, 1.540639,
     0.9482186, 1.105261, 0.1125411, 1.31828, 1.304933, 1.016301, 
        1.008043, 1.098772, 0.3921483, 1.404781, 1.214758, 1.258968, 
        0.8213903, 0.2767058, 1.430973, 0.9601138, 1.321019, 0.6648583, 
        0.3420466, 1.229267)), class = "data.frame", row.names = c(NA, 
    30L))

    我的代码:

    {ampm<-data.frame()
    amp_1m<-data.frame()
    mesor_1m<-data.frame()
    phase_1m<-data.frame()
    amp_2m<-data.frame()
    mesor_2m<-data.frame()
    phase_2m<-data.frame()
    amp_pm<-data.frame()
    mesor_pm<-data.frame()
    phase_pm<-data.frame()
    rhy_p1m<-data.frame()
    rhy_p2m<-data.frame()
    }
    for(i in 4:5){colnames(t[i])->gm
      out_im<-circacompare_mixed(x=t,col_time="time",                                            col_outcome=gm,col_group ="group",col_id="id",control=list(grouped_params=c("phi","alpha","k"),random_params=c("phi1","alpha1","k1")),period = 24,alpha_threshold = 0.05)
      out_im[[2]]$gene_symbol<-gm
      parameter_im<-as.data.frame(out_im[[2]])
      mesor1m<-slice(parameter_im,3)
      mesor2m<-slice(parameter_im,4)
      mesorpm<-slice(parameter_im,6)
      amp1m<-slice(parameter_im,7)
      amp2m<-slice(parameter_im,8)
      amppm<-slice(parameter_im,10)
      phase1m<-slice(parameter_im,11)
      phase2m<-slice(parameter_im,12)
      phasepm<-slice(parameter_im,14)
      amp_1m<-rbind(amp_1m,amp1m)
      mesor_1m<-rbind(mesor_1m,mesor1m)
      phase_1m<-rbind(phase_1m,phase1m)
      amp_2m<-rbind(amp_2m,amp2m)
      mesor_2m<-rbind(mesor_2m,mesor2m)
      phase_2m<-rbind(phase_2m,phase2m)
      amp_pm<-rbind(amp_pm,amppm)
      mesor_pm<-rbind(mesor_pm,mesorpm)
      phase_pm<-rbind(phase_pm,phasepm)
    }

    我的运行结果:

    Warning: Iteration 1, LME step: nlminb() did not converge (code = 1). Do increase 'msMaxIter'! PORT message: false convergence (8)Warning: Singular precision matrix in level -1, block 1Warning: Singular precision matrix in level -1, block . Error in nlme.formula(model = form_group, random = randomeffects_formula, :
    Unable to form Cholesky decomposition: the leading minor of order 1 is not pos.def.

    我的系统环境:

    R version 4.2.1 (2022-06-23 ucrt)
    Platform: x86_64-w64-mingw32/x64 (64-bit)
    Running under: Windows 10 x64 (build 19044)
    
    Matrix products: default
    
    locale:
    [1] LC_COLLATE=Chinese (Simplified)_China.utf8 
    [2] LC_CTYPE=Chinese (Simplified)_China.utf8   
    [3] LC_MONETARY=Chinese (Simplified)_China.utf8
    [4] LC_NUMERIC=C                               
    [5] LC_TIME=Chinese (Simplified)_China.utf8 
    
    attached base packages:
    [1] stats     graphics  grDevices utils     datasets  methods  
    [7] base     
    
    loaded via a namespace (and not attached):
      [1] fgsea_1.24.0           colorspace_2.0-3      
      [3] ggtree_3.6.2           rjson_0.2.21          
      [5] gson_0.0.9             circlize_0.4.15       
      [7] qvalue_2.30.0          XVector_0.38.0        
      [9] GlobalOptions_0.1.2    aplot_0.1.9           
     [11] clue_0.3-64            rstudioapi_0.14       
     [13] farver_2.1.1           graphlayouts_0.8.4    
     [15] ggrepel_0.9.2          bit64_4.0.5           
     [17] AnnotationDbi_1.60.0   fansi_1.0.3           
     [19] scatterpie_0.1.8       codetools_0.2-19 
    [21] splines_4.2.1          doParallel_1.0.17     
     [23] cachem_1.0.6           GOSemSim_2.24.0       
     [25] knitr_1.42             polyclip_1.10-4       
     [27] jsonlite_1.8.4         cluster_2.1.4         
     [29] GO.db_3.16.0           png_0.1-8             
     [31] ggforce_0.4.1          compiler_4.2.1        
     [33] httr_1.4.5             assertthat_0.2.1      
     [35] Matrix_1.5-3           fastmap_1.1.0         
     [37] lazyeval_0.2.2         cli_3.6.0             
     [39] tweenr_2.0.2           htmltools_0.5.4       
     [41] tools_4.2.1            igraph_1.3.5          
     [43] gtable_0.3.1           glue_1.6.2            
     [45] GenomeInfoDbData_1.2.9 reshape2_1.4.4        
     [47] dplyr_1.0.10           fastmatch_1.1-3       
     [49] Rcpp_1.0.9             enrichplot_1.18.3  
    [51] Biobase_2.58.0         vctrs_0.5.1           
     [53] Biostrings_2.66.0      ape_5.6-2             
     [55] nlme_3.1-161           iterators_1.0.14      
     [57] ggraph_2.1.0           xfun_0.36             
     [59] stringr_1.5.0          lifecycle_1.0.3       
     [61] clusterProfiler_4.6.0  DOSE_3.24.2           
     [63] zlibbioc_1.44.0        MASS_7.3-58.1         
     [65] scales_1.2.1           tidygraph_1.2.2       
     [67] parallel_4.2.1         RColorBrewer_1.1-3    
     [69] yaml_2.3.7             ComplexHeatmap_2.14.0 
     [71] memoise_2.0.1          gridExtra_2.3         
     [73] ggplot2_3.4.1          downloader_0.4        
     [75] ggfun_0.0.9            HDO.db_0.99.1         
     [77] yulab.utils_0.0.6      stringi_1.7.12        
     [79] RSQLite_2.2.20         circacompare_0.1.1    
     [81] S4Vectors_0.36.1       foreach_1.5.2         
     [83] tidytree_0.4.2         BiocGenerics_0.44.0   
     [85] BiocParallel_1.32.5    shape_1.4.6           
     [87] GenomeInfoDb_1.34.9    rlang_1.0.6           
     [89] pkgconfig_2.0.3        matrixStats_0.63.0 
    [91] bitops_1.0-7           evaluate_0.20         
     [93] lattice_0.20-45        purrr_1.0.1           
     [95] treeio_1.22.0          patchwork_1.1.2       
     [97] cowplot_1.1.1          shadowtext_0.1.2      
     [99] bit_4.0.5              tidyselect_1.2.0      
    [101] plyr_1.8.8             magrittr_2.0.3        
    [103] R6_2.5.1               IRanges_2.32.0        
    [105] generics_0.1.3         DBI_1.1.3             
    [107] pillar_1.8.1           withr_2.5.0           
    [109] KEGGREST_1.38.0        RCurl_1.98-1.9        
    [111] tibble_3.1.8           crayon_1.5.2          
    [113] utf8_1.2.2             rmarkdown_2.20        
    [115] viridis_0.6.2          GetoptLong_1.0.5      
    [117] grid_4.2.1             data.table_1.14.6     
    [119] blob_1.2.3             digest_0.6.31         
    [121] tidyr_1.2.1            gridGraphics_0.5-1    
    [123] stats4_4.2.1           munsell_0.5.0         
    [125] viridisLite_0.4.1      ggplotify_0.1.0 
  • yihui 我运行了一下这两行代码:

    .Platform

    $OS.type
    [1] "windows"

    $file.sep
    [1] "/"

    $dynlib.ext
    [1] ".dll"

    $GUI
    [1] "RStudio"

    $endian
    [1] "little"

    $pkgType
    [1] "win.binary"

    $path.sep
    [1] ";"

    $r_arch
    [1] "x64"

    list.files(system.file('libs', package = 'xfun'), recursive = TRUE)

    [1] "x64/symbols.rds" "x64/xfun.dll"

    看上去好像没什么问题。
    我几天前把包的安装路径和加载路径统一成一个路径了,现在包安装路径是这个:

    .libPaths()

    [1] "D:/APP/R-4.2.1/library"

    后来又安装了Rtools

    我不知道这会不会有影响,比如r包安装目录权限方面的问题,导致rstudio无法识别某些DLL“R包”。
    今天我重新安装AnnotationDbi

    install.packages("D:/R_packages/AnnotationDbi",repos=NULL, type="source",denpendencies=T)

    Error: package or namespace load failed for ‘AnnotationDbi’:
    loadNamespace()里算'zlibbioc'时.onLoad失败了,详细内容:
    调用: inDL(x, as.logical(local), as.logical(now), ...)
    错误: unable to load shared object 'D:/APP/R-4.2.1/library/zlibbioc/libs/x64/zlib1bioc.dll':
    LoadLibrary failure: 找不到指定的模块。

    library(zlibbioc)

    Error: package or namespace load failed for ‘zlibbioc’:
    loadNamespace()里算'zlibbioc'时.onLoad失败了,详细内容:
    调用: inDL(x, as.logical(local), as.logical(now), ...)
    错误: unable to load shared object 'D:/APP/R-4.2.1/library/zlibbioc/libs/x64/zlib1bioc.dll':
    LoadLibrary failure: 找不到指定的模块。

    if (!require("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install("zlibbioc",force = TRUE)

    安装成功
    这次我没有用install.packages("D:/R_packages/AnnotationDbi",repos=NULL, type="source",denpendencies=T)
    所以也没有出现这种报错:

    Error in library.dynam(lib, package, package.lib) :
    DLL 'XVector' not found: maybe not installed for this architecture?

    但有另一种报错/(ㄒoㄒ)/~

    if (!require("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install("AnnotationDbi",force = TRUE)

    Warning messages:
    1: In loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[]) :
    package ‘stringi’ has no 'package.rds' in Meta/
    2: In loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[]) :
    package ‘stringi’ has no 'package.rds' in Meta/
    'getOption("repos")' replaces Bioconductor standard
    repositories, see '?repositories' for details
    replacement repositories:
    CRAN: https://mirrors.sustech.edu.cn/CRAN/
    Warning: URL 'https://mirrors.sustech.edu.cn/CRAN/src/contrib/PACKAGES.rds': status was 'Failure when receiving data from the peer'

  • yihui 对,这实在是麻烦。
    我检查了一下getOption('repos'),它反馈:

    CRAN
    "https://mirrors.tuna.tsinghua.edu.cn/CRAN/"
    attr(,"RStudio")
    [1] TRUE

    后面我重新安装了xfun,但后续又出现一个接一个的这样的报错:Error in library.dynam(lib, package, package.lib) :
    DLL 'R包名' not found: maybe not installed for this architecture?
    我就只能一个一个地重新安装这些明明已经安装好的包/(ㄒoㄒ)/~,好费时间哇,到现在也没能把包穷尽可我实在是不清楚哪里出问题了(T_T)

    • ##问题描述
      用BioManager包安装org.eg.Mm.db包失败,提示xfun包为架构安装,但xfun包其实已安装。

      ##我的代码、数据和运行结果

      .libPaths()

      [1] "D:/APP/R-4.2.1/library"

      library(BiocManager)
      BiocManager::install("org.eg.Mm.db")

      Error in library.dynam(lib, package, package.lib) : 没有这个DLL ‘xfun’:是不是没有为此架构安装?

      library(xfun)

      Warning: 程辑包‘xfun’是用R版本4.2.2 来建造的
      Error: package or namespace load failed for ‘xfun’ in library.dynam(lib, package, package.lib):
      没有这个DLL ‘xfun’:是不是没有为此架构安装?

      ##我的初步解决方法

      在Rstudio界面点击Tools>Check for Package Upates>Select All>Install Updates

      反馈:
      无法将拆除原来安装的程序包‘digest’
      Warning in install.packages :
      problem copying D:\APP\R-4.2.1\library\00LOCK\digest\demo\vectorised.R to D:\APP\R-4.2.1\library\digest\demo\vectorised.R: Permission denied
      下载的二进制程序包在
      C:\Users\86157\AppData\Local\Temp\RtmpEzy9GL\downloaded_packages里

      ##我的系统环境

      SessionInfo()

      *R version 4.2.1 (2022-06-23 ucrt)
      Platform: x86_64-w64-mingw32/x64 (64-bit)
      Running under: Windows 10 x64 (build 19044)

      Matrix products: default

      locale:
      [1] LC_COLLATE=Chinese (Simplified)China.utf8
      [2] LC_CTYPE=Chinese (Simplified)
      China.utf8
      [3] LC_MONETARY=Chinese (Simplified)China.utf8
      [4] LC_NUMERIC=C
      [5] LC_TIME=Chinese (Simplified)
      China.utf8

      attached base packages:
      [1] stats graphics grDevices utils datasets methods
      [7] base

      loaded via a namespace (and not attached):
      [1] evaluate_0.19 data.table_1.14.6 tools_4.2.1
      [4] compiler_4.2.1 BiocManager_1.30.19*