Let’s take a look at the reads that overlap rs9536314 for sample NA12893 within the Illumina Platinum Genomes dataset. This SNP resides on chromosome 13 at position 33628137 in 0-based coordinates.
# Authenticated on package load from the env variable GOOGLE_API_KEY.
suppressPackageStartupMessages(library(GoogleGenomics))
## Configured public API key.
reads <- getReads(readGroupSetId="CMvnhpKTFhDyy__v0qfPpkw",
chromosome="chr13",
start=33628130,
end=33628145)
## Fetching reads page.
## Note: the specification for S3 class "AsIs" in package 'jsonlite' seems equivalent to one from package 'BiocGenerics': not turning on duplicate class definitions for this class.
## Reads are now available.
alignments <- readsToGAlignments(reads)
Display the basic alignments and coverage data:
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(ggbio))
alignmentPlot <- autoplot(alignments, aes(color=strand, fill=strand))
## Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale.
## Scale for 'fill' is already present. Adding another scale for 'fill', which will replace the existing scale.
coveragePlot <- ggplot(as(alignments, "GRanges")) +
stat_coverage(color="gray40", fill="skyblue")
tracks(alignmentPlot, coveragePlot,
xlab="Reads overlapping rs9536314 for NA12893")
You could also display the spot on the chromosome these alignments came from:
ideogramPlot <- plotIdeogram(genome="hg19", subchr="chr13")
ideogramPlot + xlim(as(alignments, "GRanges"))
Package versions used:
sessionInfo()
## R version 3.2.0 (2015-04-16)
## Platform: x86_64-unknown-linux-gnu (64-bit)
## Running under: Ubuntu 14.04.2 LTS
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 parallel stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] ggbio_1.16.0 ggplot2_1.0.1
## [3] GoogleGenomics_1.0.0 VariantAnnotation_1.14.0
## [5] GenomicAlignments_1.4.0 Rsamtools_1.20.0
## [7] Biostrings_2.36.0 XVector_0.8.0
## [9] GenomicRanges_1.20.0 GenomeInfoDb_1.4.0
## [11] IRanges_2.2.0 S4Vectors_0.6.0
## [13] BiocGenerics_0.14.0 BiocStyle_1.6.0
##
## loaded via a namespace (and not attached):
## [1] reshape2_1.4.1 splines_3.2.0 lattice_0.20-31
## [4] colorspace_1.2-6 htmltools_0.2.6 rtracklayer_1.28.0
## [7] yaml_2.1.13 GenomicFeatures_1.20.0 RBGL_1.44.0
## [10] XML_3.98-1.1 survival_2.38-1 foreign_0.8-63
## [13] DBI_0.3.1 BiocParallel_1.2.0 RColorBrewer_1.1-2
## [16] lambda.r_1.1.7 plyr_1.8.1 stringr_0.6.2
## [19] zlibbioc_1.14.0 munsell_0.4.2 gtable_0.1.2
## [22] futile.logger_1.4 OrganismDbi_1.10.0 evaluate_0.6
## [25] labeling_0.3 latticeExtra_0.6-26 Biobase_2.28.0
## [28] knitr_1.9 GGally_0.5.0 biomaRt_2.24.0
## [31] AnnotationDbi_1.30.0 proto_0.3-10 Rcpp_0.11.5
## [34] acepack_1.3-3.3 scales_0.2.4 BSgenome_1.36.0
## [37] formatR_1.1 graph_1.46.0 Hmisc_3.15-0
## [40] jsonlite_0.9.16 gridExtra_0.9.1 rjson_0.2.15
## [43] digest_0.6.8 biovizBase_1.16.0 grid_3.2.0
## [46] tools_3.2.0 bitops_1.0-6 RCurl_1.95-4.5
## [49] RSQLite_1.0.0 dichromat_2.0-0 Formula_1.2-1
## [52] cluster_2.0.1 futile.options_1.0.0 MASS_7.3-40
## [55] rmarkdown_0.5.1 reshape_0.8.5 httr_0.6.1
## [58] rpart_4.1-9 nnet_7.3-9