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Hi, I am just trying now to run PCAir and PCRelate. However, I ran into a problem that I am not sure how to fix.
When I run pcair(), I get the following error (highlighted in bold):
Using kinobj and divobj to partition samples into unrelated and related sets
Working with 425 samples
Identifying relatives for each sample using kinship threshold 0.0441941738241592
Identifying pairs of divergent samples using divergence threshold -0.0441941738241592
Partitioning samples into unrelated and related sets...
Unrelated Set: 375 Samples
Related Set: 50 Samples
Performing PCA on the Unrelated Set...
Principal Component Analysis (PCA) on genotypes:
**Excluding 8,685 SNPs on non-autosomes**
**Error in .InitFile2(cmd = "Principal Component Analysis (PCA) on genotypes:", :
There is no SNP!**
The code I used is below:
# GDS file obtained from a genlight object (dartR package) with the dartR::gl2gds" function. Then GDS file converted into gdsobj with the code below (from GDWAS tools package):
mydataset_geno <- GdsGenotypeReader(filename = "C:/documents/mydataset_GDS.gds")
class(mydataset_geno) # [1] "GdsGenotypeReader" attr(,"package") [1] "GWASTools"
# object without annotation
mydataset_genoData <- GenotypeData(mydataset_geno)
str(mydataset_genoData)
Formal class 'GenotypeData' [package "GWASTools"] with 3 slots
..@ data :Formal class 'GdsGenotypeReader' [package "GWASTools"] with 15 slots
.. .. ..@ snpIDvar : chr "snp.id"
.. .. ..@ chromosomeVar: chr "snp.chromosome"
.. .. ..@ positionVar : chr "snp.position"
.. .. ..@ scanIDvar : chr "sample.id"
.. .. ..@ genotypeVar : chr "genotype"
.. .. ..@ alleleVar : chr "snp.allele"
.. .. ..@ autosomeCode : int [1:22] 1 2 3 4 5 6 7 8 9 10 ...
.. .. ..@ XchromCode : int 23
.. .. ..@ YchromCode : int 25
.. .. ..@ XYchromCode : int 24
.. .. ..@ MchromCode : int 26
.. .. ..@ genotypeDim : chr "snp,scan"
.. .. ..@ missingValue : int 3
.. .. ..@ filename : chr "C:/documents/mydataset"| __truncated__
.. .. ..@ handler :List of 5
.. .. .. ..$ filename: chr "C:/documents/mydataset_GDS.gds_LocusC"| __truncated__
.. .. .. ..$ id : int 1
.. .. .. ..$ ptr :<externalptr>
.. .. .. ..$ root : 'gdsn.class' raw [1:20] 08 00 00 00 ...
.. .. .. ..$ readonly: logi TRUE
.. .. .. ..- attr(*, "class")= chr "gds.class"
..@ snpAnnot : NULL
..@ scanAnnot: NULL
# PCAir
mydataset_pca_PCAir <- pcair(
mydataset_genoData,
kinobj = mydataset_kingMat,
kin.thresh=2^(-9/2), # = 0.04 = 3rd degree kinship threshold, which corresponds to first cousins (actually 1stcousins kinship= 1/16 - Weir 2006 & 0.06>0.04)
divobj = mydataset_kingMat,
div.thresh=-2^(-9/2))
Using kinobj and divobj to partition samples into unrelated and related sets
Working with 425 samples
Identifying relatives for each sample using kinship threshold 0.0441941738241592
Identifying pairs of divergent samples using divergence threshold -0.0441941738241592
Partitioning samples into unrelated and related sets...
Unrelated Set: 375 Samples
Related Set: 50 Samples
Performing PCA on the Unrelated Set...
Principal Component Analysis (PCA) on genotypes:
**Excluding 8,685 SNPs on non-autosomes
Error in .InitFile2(cmd = "Principal Component Analysis (PCA) on genotypes:", :
There is no SNP!**
How to make sure that all SNPs are used in PCAir and not only Autosomes (as my SNPs have no chromosome position being a non-model species with no genome)?
Thank you for any help! Gabriella
**sessionInfo( ):**
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.utf8 LC_CTYPE=English_Australia.utf8 LC_MONETARY=English_Australia.utf8
[4] LC_NUMERIC=C LC_TIME=English_Australia.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] GENESIS_2.26.0 GWASTools_1.42.1 Biobase_2.56.0 BiocGenerics_0.42.0 InRelate_0.1.0
[6] remotes_2.4.2 fstcore_0.9.12 radiator_1.2.8 OutFLANK_0.2 LEA_3.8.0
[11] vcfR_1.12.0 stockR_1.0.74 qvalue_2.28.0 SNPRelate_1.30.1 dartR_2.0.4
[16] adegenet_2.1.7 ade4_1.7-19 plotrix_3.8-2 forcats_0.5.1 stringr_1.4.1
[21] dplyr_1.0.9 purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7
[26] tidyverse_1.3.1 ggplot2_3.4.0 plyr_1.8.7 SeqArray_1.36.3 gdsfmt_1.32.0
loaded via a namespace (and not attached):
[1] utf8_1.2.2 R.utils_2.12.0 tidyselect_1.1.2 RSQLite_2.3.2
[5] BiocParallel_1.30.4 grid_4.2.1 combinat_0.0-8 StAMPP_1.6.3
[9] GWASExactHW_1.01 devtools_2.4.3 munsell_0.5.0 codetools_0.2-18
[13] withr_2.5.0 colorspace_2.0-3 fst_0.9.8 pegas_1.1
[17] knitr_1.39 rstudioapi_0.13 stats4_4.2.1 labeling_0.4.2
[21] RgoogleMaps_1.4.5.3 logistf_1.26.0 GenomeInfoDbData_1.2.8 bit64_4.0.5
[25] farver_2.1.1 gap.datasets_0.0.5 rprojroot_2.0.3 vctrs_0.5.1
[29] generics_0.1.3 xfun_0.31 R6_2.5.1 doParallel_1.0.17
[33] GenomeInfoDb_1.32.2 fields_14.0 bitops_1.0-7 cachem_1.0.6
[37] reshape_0.8.9 assertthat_0.2.1 promises_1.2.0.1 scales_1.2.0
[41] vroom_1.5.7 pinfsc50_1.2.0 gtable_0.3.0 formula.tools_1.7.1
[45] processx_3.7.0 spam_2.9-0 sandwich_3.0-2 MatrixModels_0.5-0
[49] rlang_1.0.6 calibrate_1.7.7 splines_4.2.1 rgdal_1.5-32
[53] hexbin_1.28.2 broom_1.0.0 BiocManager_1.30.18 reshape2_1.4.4
[57] modelr_0.1.8 backports_1.4.1 httpuv_1.6.5 tools_4.2.1
[61] usethis_2.1.6 ellipsis_0.3.2 raster_3.5-21 RColorBrewer_1.1-3
[65] DNAcopy_1.70.0 sessioninfo_1.2.2 Rcpp_1.0.9 zlibbioc_1.42.0
[69] RCurl_1.98-1.7 ps_1.7.1 prettyunits_1.1.1 viridis_0.6.2
[73] zoo_1.8-12 S4Vectors_0.34.0 haven_2.5.0 cluster_2.1.3
[77] fs_1.5.2 magrittr_2.0.3 SeqVarTools_1.34.0 data.table_1.14.2
[81] SparseM_1.81 genetics_1.3.8.1.3 lmtest_0.9-40 reprex_2.0.1
[85] mvtnorm_1.1-3 pkgload_1.3.0 hms_1.1.1 patchwork_1.1.1
[89] mime_0.12 xtable_1.8-4 readxl_1.4.0 IRanges_2.30.0
[93] gridExtra_2.3 compiler_4.2.1 mice_3.14.0 maps_3.4.0
[97] crayon_1.5.1 gdistance_1.3-6 R.oo_1.25.0 htmltools_0.5.2
[101] mgcv_1.8-40 later_1.3.0 tzdb_0.3.0 lubridate_1.8.0
[105] DBI_1.1.3 dbplyr_2.2.1 PopGenReport_3.0.7 MASS_7.3-57
[109] Matrix_1.4-1 permute_0.9-7 cli_3.4.1 R.methodsS3_1.8.2
[113] gdata_2.18.0.1 parallel_4.2.1 dotCall64_1.0-1 igraph_1.3.2
[117] GenomicRanges_1.48.0 pkgconfig_2.0.3 sp_1.5-0 terra_1.5-34
[121] versions_0.3 xml2_1.3.3 foreach_1.5.2 XVector_0.36.0
[125] rvest_1.0.2 quantsmooth_1.62.0 callr_3.7.1 digest_0.6.29
[129] vegan_2.6-2 Biostrings_2.64.0 cellranger_1.1.0 operator.tools_1.6.3
[133] curl_4.3.2 gap_1.2.3-6 quantreg_5.93 shiny_1.7.1
[137] gtools_3.9.3 lifecycle_1.0.3 nlme_3.1-157 dismo_1.3-5
[141] jsonlite_1.8.0 seqinr_4.2-16 viridisLite_0.4.0 fansi_1.0.3
[145] pillar_1.7.0 lattice_0.20-45 GGally_2.1.2 survival_3.3-1
[149] fastmap_1.1.0 httr_1.4.3 pkgbuild_1.3.1 glue_1.6.2
[153] mmod_1.3.3 png_0.1-7 iterators_1.0.14 bit_4.0.4
[157] stringi_1.7.8 blob_1.2.3 memoise_2.0.1 ape_5.6-2
