Question: gwascat: error regarding mismatched genome builds when using makeCurrentGwascat()
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gravatar for maya.kappil
29 days ago by
maya.kappil10
maya.kappil10 wrote:

Hello,

I was able to match some disease traits to SNPs I'm interested in based on the NHGRI GWAS catalog website, and I'm now interested to use the gwascat R package to plot my findings with these GWAS hits. These GWAS hits were published relatively recently, so I'm not able to utilize the preloaded ebicat38 dataset. However, I run into an error when loading a more current dataset using makeCurrentGwascat(). I'm wondering if there is anything I should change in the following script to overcome the error. Thank you!

library(gwascat)

load current version of GWAS catalog

newcatr<-makeCurrentGwascat(genome="GRCh38")

ACSL3 GRCh38/hg38 coordinates

chr<-'chr2' from<-222860934 to<- 222944639

ACSL3_anno = GRanges(seqnames=chr, ranges=IRanges(start=from,end=to))

match formatting of both GRanges

seqlevelsStyle(ACSL3anno) = "UCSC" seqlevelsStyle(newcatr) = "UCSC" genome(ACSL3anno)<-"GRCh38" genome(newcatr)<-"GRCh38"

check genome builds match

ACSL3_anno *GRanges object with 1 range and 0 metadata columns: seqnames ranges strand <rle> <iranges> <rle> [1] chr2 222860934-222944639 *


seqinfo: 1 sequence from GRCh38 genome; no seqlengths*

newcatr gwasloc instance with 6 records and 38 attributes per record. Extracted: 2019-07-19 Genome: GRCh38 Excerpt: GRanges object with 5 ranges and 3 metadata columns: seqnames ranges strand | <rle> <iranges> <rle> | [1] chr6 32251212 * | [2] chr6 32441753 * | [3] chr6 33075103 * |

basic = gwcex2gviz(basegr = newcatr, contextGR=ACSL3_anno,plot.it=FALSE)

Error in mergeNamedAtomicVectors(genome(x), genome(y), what = c("sequence", : sequence chr2 has incompatible genomes: - in 'x': hg19 - in 'y': GRCh38

sessionInfo() R version 3.5.3 (2019-03-11) Platform: x86_64-pc-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core)

Matrix products: default BLAS/LAPACK: /hpc/packages/minerva-centos7/intel/parallelstudioxe2019/compilersandlibraries2019.0.117/linux/mkl/lib/intel64lin/libmklgf_lp64.so

locale: [1] LCCTYPE=enUS.UTF-8 LCNUMERIC=C [3] LCTIME=enUS.UTF-8 LCCOLLATE=enUS.UTF-8 [5] LCMONETARY=enUS.UTF-8 LCMESSAGES=enUS.UTF-8 [7] LCPAPER=enUS.UTF-8 LCNAME=C [9] LCADDRESS=C LCTELEPHONE=C [11] LCMEASUREMENT=enUS.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets [8] methods base

other attached packages: [1] TxDb.Hsapiens.UCSC.hg38.knownGene3.4.0 [2] gwascat2.14.0 [3] Homo.sapiens1.3.1 [4] TxDb.Hsapiens.UCSC.hg19.knownGene3.2.2 [5] org.Hs.eg.db3.7.0 [6] GO.db3.7.0 [7] OrganismDbi1.24.0 [8] GenomicFeatures1.34.8 [9] GenomicRanges1.34.0 [10] GenomeInfoDb1.18.2 [11] AnnotationDbi1.44.0 [12] IRanges2.16.0 [13] S4Vectors0.20.1 [14] Biobase2.42.0 [15] BiocGenerics_0.28.0

loaded via a namespace (and not attached): [1] backports1.1.4 AnnotationHub2.14.5 [3] Hmisc4.2-0 fastmatch1.1-0 [5] gQTLstats1.14.1 plyr1.8.4 [7] lazyeval0.2.2 splines3.5.3 [9] BatchJobs1.8 BiocParallel1.16.6 [11] ggplot23.2.0 digest0.6.20 [13] foreach1.4.4 ensembldb2.6.8 [15] htmltools0.3.6 magrittr1.5 [17] checkmate1.9.4 memoise1.1.0 [19] BBmisc1.11 BSgenome1.50.0 [21] cluster2.0.7-1 doParallel1.0.14 [23] limma3.38.3 Biostrings2.50.2 [25] matrixStats0.54.0 ggbio1.30.0 [27] prettyunits1.0.2 colorspace1.4-1 [29] blob1.2.0 xfun0.8 [31] dplyr0.8.3 crayon1.3.4 [33] RCurl1.95-4.12 jsonlite1.6 [35] graph1.60.0 ffbase0.12.7 [37] zeallot0.1.0 brew1.0-6 [39] survival2.43-3 sendmailR1.2-1 [41] VariantAnnotation1.28.13 iterators1.0.10 [43] glue1.3.1 gtable0.3.0 [45] zlibbioc1.28.0 XVector0.22.0 [47] DelayedArray0.8.0 scales1.0.0 [49] DBI1.0.0 GGally1.4.0 [51] Rcpp1.0.1 viridisLite0.3.0 [53] xtable1.8-4 progress1.2.2 [55] htmlTable1.13.1 foreign0.8-71 [57] bit1.1-14 Formula1.2-3 [59] erma0.14.0 htmlwidgets1.3 [61] httr1.4.0 RColorBrewer1.1-2 [63] acepack1.4.1 ff2.2-14 [65] pkgconfig2.0.2 reshape0.8.8 [67] XML3.98-1.20 Gviz1.26.5 [69] nnet7.3-12 tidyselect0.2.5 [71] rlang0.4.0 reshape21.4.3 [73] later0.8.0 sQTLseekeR2.1 [75] munsell0.5.0 tools3.5.3 [77] RSQLite2.1.1 stringr1.4.0 [79] yaml2.2.0 knitr1.23 [81] bit640.9-7 purrr0.3.2 [83] AnnotationFilter1.6.0 RBGL1.58.2 [85] nlme3.1-137 mime0.7 [87] biomaRt2.38.0 compiler3.5.3 [89] rstudioapi0.10 interactiveDisplayBase1.20.0 [91] beeswarm0.2.3 plotly4.9.0 [93] curl3.3 tibble2.1.3 [95] stringi1.4.3 GenomicFiles1.18.0 [97] lattice0.20-38 ProtGenerics1.14.0 [99] Matrix1.2-15 vctrs0.2.0 [101] pillar1.4.2 BiocManager1.30.4 [103] snpStats1.32.0 data.table1.12.2 [105] bitops1.0-6 httpuv1.5.1 [107] rtracklayer1.42.2 R62.4.0 [109] latticeExtra0.6-28 promises1.0.1 [111] gridExtra2.3 vipor0.4.5 [113] codetools0.2-16 dichromat2.0-0 [115] assertthat0.2.1 SummarizedExperiment1.12.0 [117] GenomicAlignments1.18.1 Rsamtools1.34.1 [119] GenomeInfoDbData1.2.0 mgcv1.8-27 [121] hms0.5.0 gQTLBase1.14.0 [123] grid3.5.3 rpart4.1-13 [125] tidyr0.8.3 biovizBase1.30.1 [127] shiny1.3.2 base64enc0.1-3 [129] ggbeeswarm_0.6.0

gwascat • 61 views
ADD COMMENTlink written 29 days ago by maya.kappil10
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