The liftOver facilities developed in conjunction with the UCSC browser track infrastructure are available for transforming data in GRanges formats. This is illustrated here with an image of the NHGRI GWAS catalog that is, as of Oct. 31 2014, distributed with coordinates defined by NCBI build hg38.
## Loading required package: Homo.sapiens## Loading required package: AnnotationDbi## Loading required package: stats4## Loading required package: BiocGenerics## Loading required package: parallel##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:parallel':
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## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB## The following objects are masked from 'package:stats':
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## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
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## Filter, Find, Map, Position, Reduce, anyDuplicated, append,
## as.data.frame, cbind, colMeans, colSums, colnames, do.call,
## duplicated, eval, evalq, get, grep, grepl, intersect,
## is.unsorted, lapply, lengths, mapply, match, mget, order,
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## union, unique, unsplit, which, which.max, which.min## Loading required package: Biobase## Welcome to Bioconductor
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## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.## Loading required package: IRanges## Loading required package: S4Vectors##
## Attaching package: 'S4Vectors'## The following object is masked from 'package:base':
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## expand.grid## Loading required package: OrganismDbi## Loading required package: GenomicFeatures## Loading required package: GenomeInfoDb## Loading required package: GenomicRanges## Loading required package: GO.db## ## Loading required package: org.Hs.eg.db## ## Loading required package: TxDb.Hsapiens.UCSC.hg19.knownGene## gwascat loaded. Use data(ebicat38) for hg38 coordinates;## data(ebicat37) for hg19 coordinates.library(gwascat)
cur = makeCurrentGwascat() # result varies by daycur## gwasloc instance with 17865 records and 35 attributes per record.
## Extracted: 2014-10-31
## Genome: GRCh38
## Excerpt:
## GRanges object with 5 ranges and 35 metadata columns:
## seqnames ranges strand | Date.Added.to.Catalog
## <Rle> <IRanges> <Rle> | <character>
## [1] 17 [79831041, 79831041] * | 10/22/2014
## [2] 5 [31766326, 31766326] * | 10/22/2014
## [3] 11 [13107616, 13107616] * | 10/22/2014
## [4] 10 [94922089, 94922089] * | 10/22/2014
## [5] 10 [94922089, 94922089] * | 10/22/2014
## PUBMEDID First.Author Date Journal
## <integer> <character> <character> <character>
## [1] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [2] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [3] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [4] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [5] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## Link
## <character>
## [1] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [2] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [3] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [4] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [5] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## Study
## <character>
## [1] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [2] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [3] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [4] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [5] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## Disease.Trait
## <character>
## [1] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [2] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [3] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [4] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [5] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## Initial.Sample.Description
## <character>
## [1] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [2] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [3] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [4] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [5] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## Replication.Sample.Description Region Chr_id Chr_pos
## <character> <character> <character> <numeric>
## [1] <NA> 17q25.3 17 79831041
## [2] <NA> 5p13.3 5 31766326
## [3] <NA> 11p15.2 11 13107616
## [4] <NA> 10q23.33 10 94922089
## [5] <NA> 10q23.33 10 94922089
## Reported.Gene.s. Mapped_gene Upstream_gene_id
## <character> <character> <character>
## [1] CBX4 CBX8 - CBX4 57332
## [2] PDZD2 PDZD2 <NA>
## [3] CTC-497E21.5 RASSF10 - ARNTL 644943
## [4] CYP2C19,CYP2C9 CYP2C115P - CYP2C9 100874513
## [5] CYP2C19,CYP2C9 CYP2C115P - CYP2C9 100874513
## Downstream_gene_id Snp_gene_ids Upstream_gene_distance
## <character> <character> <character>
## [1] 8535 33.93
## [2] <NA> 23037 <NA>
## [3] 406 95.51
## [4] 1559 15.96
## [5] 1559 15.96
## Downstream_gene_distance Strongest.SNP.Risk.Allele SNPs
## <character> <character> <character>
## [1] 2.12 rs9747992-? rs9747992
## [2] <NA> rs2059865-? rs2059865
## [3] 170.12 rs117020818-? rs117020818
## [4] 16.5 rs1074145-? rs1074145
## [5] 16.5 rs1074145-? rs1074145
## Merged Snp_id_current Context Intergenic
## <character> <character> <character> <character>
## [1] 0 9747992 Intergenic 1
## [2] 0 2059865 intron 0
## [3] 0 117020818 Intergenic 1
## [4] 0 1074145 Intergenic 1
## [5] 0 1074145 Intergenic 1
## Risk.Allele.Frequency p.Value Pvalue_mlog p.Value..text.
## <character> <numeric> <numeric> <character>
## [1] 0.086 2e-07 6.698970 (S-DCT concentration)
## [2] 0.235 3e-07 6.522879 (S-DCT concentration)
## [3] 0.046 7e-07 6.154902 (S-DCT concentration)
## [4] 0.162 4e-09 8.397940 (S-CT concentration)
## [5] 0.162 2e-16 15.698970 (S-DCT/S-CT ratio)
## OR.or.beta X95..CI..text. Platform..SNPs.passing.QC. CNV
## <numeric> <character> <character> <character>
## [1] <NA> NR Illumina [7,537,437] (Imputed) N
## [2] <NA> NR Illumina [7,537,437] (Imputed) N
## [3] <NA> NR Illumina [7,537,437] (Imputed) N
## [4] <NA> NR Illumina [7,537,437] (Imputed) N
## [5] <NA> NR Illumina [7,537,437] (Imputed) N
## num.Risk.Allele.Frequency
## <numeric>
## [1] 0.086
## [2] 0.235
## [3] 0.046
## [4] 0.162
## [5] 0.162
## -------
## seqinfo: 23 sequences from GRCh38 genomeThe transformation to hg19 coordinates is defined by a chain file provided by UCSC. rtracklayer::import.chain will bring the data into R.
library(rtracklayer)
ch = import.chain("hg38ToHg19.over.chain")
ch## Chain of length 25
## names(25): chr22 chr21 chr19 chr20 chrY chr18 ... chr5 chr4 chr3 chr2 chr1str(ch[[1]])## Formal class 'ChainBlock' [package "rtracklayer"] with 6 slots
## ..@ ranges :Formal class 'IRanges' [package "IRanges"] with 6 slots
## .. .. ..@ start : int [1:6842] 16367189 16386933 16386970 16387001 16387128 16395491 16395528 16395841 16395860 16395956 ...
## .. .. ..@ width : int [1:6842] 19744 36 31 112 8362 36 312 18 95 33 ...
## .. .. ..@ NAMES : NULL
## .. .. ..@ elementType : chr "integer"
## .. .. ..@ elementMetadata: NULL
## .. .. ..@ metadata : list()
## ..@ offset : int [1:6842] -480662 -480702 -480702 -480726 -480726 -480726 -480726 -480726 -480726 -480726 ...
## ..@ score : int [1:1168] -1063867308 68830488 21156147 20814926 7358950 3927744 2928210 991419 880681 802146 ...
## ..@ space : chr [1:1168] "chr22" "chr14" "chr22" "chr21" ...
## ..@ reversed: logi [1:1168] FALSE FALSE FALSE FALSE FALSE FALSE ...
## ..@ length : int [1:1168] 1124 1280 173 465 398 110 43 173 342 84 ...Some more details about the chain data structure are available in the import.chain man page
A chain file essentially details many local alignments, so it is possible for the "from" ranges to map to overlapping regions in the other sequence. The "from" ranges are guaranteed to be disjoint (but do not necessarily cover the entire "from" sequence).
The liftOver function will create a GRangesList.
seqlevelsStyle(cur) = "UCSC" # necessary
cur19 = liftOver(cur, ch)## Warning: closing unused connection 5 (hg38ToHg19.over.chain)class(cur19)## [1] "GRangesList"
## attr(,"package")
## [1] "GenomicRanges"We unlist and coerce to the gwaswloc class, a convenient form for the GWAS catalog with its many mcols fields.
cur19 = unlist(cur19)
genome(cur19) = "hg19"
cur19 = new("gwaswloc", cur19)
cur19## gwasloc instance with 17845 records and 35 attributes per record.
## Extracted:
## Genome: hg19
## Excerpt:
## GRanges object with 5 ranges and 35 metadata columns:
## seqnames ranges strand | Date.Added.to.Catalog
## <Rle> <IRanges> <Rle> | <character>
## [1] chr17 [77804840, 77804840] * | 10/22/2014
## [2] chr5 [31766433, 31766433] * | 10/22/2014
## [3] chr11 [13129163, 13129163] * | 10/22/2014
## [4] chr10 [96681846, 96681846] * | 10/22/2014
## [5] chr10 [96681846, 96681846] * | 10/22/2014
## PUBMEDID First.Author Date Journal
## <integer> <character> <character> <character>
## [1] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [2] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [3] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [4] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## [5] 24528284 Ji Y 08/01/2014 Br J Clin Pharmacol
## Link
## <character>
## [1] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [2] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [3] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [4] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## [5] http://www.ncbi.nlm.nih.gov/pubmed/24528284
## Study
## <character>
## [1] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [2] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [3] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [4] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## [5] Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.
## Disease.Trait
## <character>
## [1] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [2] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [3] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [4] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## [5] Response to serotonin reuptake inhibitors in major depressive disorder (plasma drug and metabolite levels)
## Initial.Sample.Description
## <character>
## [1] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [2] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [3] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [4] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## [5] 300 European ancestry Escitalpram treated individuals, 130 European ancestry Citalopram treated individuals
## Replication.Sample.Description Region Chr_id Chr_pos
## <character> <character> <character> <numeric>
## [1] <NA> 17q25.3 17 79831041
## [2] <NA> 5p13.3 5 31766326
## [3] <NA> 11p15.2 11 13107616
## [4] <NA> 10q23.33 10 94922089
## [5] <NA> 10q23.33 10 94922089
## Reported.Gene.s. Mapped_gene Upstream_gene_id
## <character> <character> <character>
## [1] CBX4 CBX8 - CBX4 57332
## [2] PDZD2 PDZD2 <NA>
## [3] CTC-497E21.5 RASSF10 - ARNTL 644943
## [4] CYP2C19,CYP2C9 CYP2C115P - CYP2C9 100874513
## [5] CYP2C19,CYP2C9 CYP2C115P - CYP2C9 100874513
## Downstream_gene_id Snp_gene_ids Upstream_gene_distance
## <character> <character> <character>
## [1] 8535 33.93
## [2] <NA> 23037 <NA>
## [3] 406 95.51
## [4] 1559 15.96
## [5] 1559 15.96
## Downstream_gene_distance Strongest.SNP.Risk.Allele SNPs
## <character> <character> <character>
## [1] 2.12 rs9747992-? rs9747992
## [2] <NA> rs2059865-? rs2059865
## [3] 170.12 rs117020818-? rs117020818
## [4] 16.5 rs1074145-? rs1074145
## [5] 16.5 rs1074145-? rs1074145
## Merged Snp_id_current Context Intergenic
## <character> <character> <character> <character>
## [1] 0 9747992 Intergenic 1
## [2] 0 2059865 intron 0
## [3] 0 117020818 Intergenic 1
## [4] 0 1074145 Intergenic 1
## [5] 0 1074145 Intergenic 1
## Risk.Allele.Frequency p.Value Pvalue_mlog p.Value..text.
## <character> <numeric> <numeric> <character>
## [1] 0.086 2e-07 6.698970 (S-DCT concentration)
## [2] 0.235 3e-07 6.522879 (S-DCT concentration)
## [3] 0.046 7e-07 6.154902 (S-DCT concentration)
## [4] 0.162 4e-09 8.397940 (S-CT concentration)
## [5] 0.162 2e-16 15.698970 (S-DCT/S-CT ratio)
## OR.or.beta X95..CI..text. Platform..SNPs.passing.QC. CNV
## <numeric> <character> <character> <character>
## [1] <NA> NR Illumina [7,537,437] (Imputed) N
## [2] <NA> NR Illumina [7,537,437] (Imputed) N
## [3] <NA> NR Illumina [7,537,437] (Imputed) N
## [4] <NA> NR Illumina [7,537,437] (Imputed) N
## [5] <NA> NR Illumina [7,537,437] (Imputed) N
## num.Risk.Allele.Frequency
## <numeric>
## [1] 0.086
## [2] 0.235
## [3] 0.046
## [4] 0.162
## [5] 0.162
## -------
## seqinfo: 23 sequences from hg19 genome; no seqlengthsWe see that the translation leads to a loss of some loci.
length(cur)-length(cur19)## [1] 20setdiff(cur$SNPs, cur19$SNPs)## [1] "rs687289" "rs386000" "rs718433" "rs4911642" "rs687621"
## [6] "rs757210" "rs11672691" "rs644234" "rs514659" "rs9876781"
## [11] "rs649129" "rs1167796" "rs644148"It may be interesting to follow up some of the losses.