Sequence difference plot
Here we use the data published in Potato Research
(Chang et al. 2015) as an example.
fas <- list.files(system.file("examples","GVariation", package="seqcombo"),
pattern="fas", full.names=TRUE)
fas
## [1] "/tmp/RtmpP5ZN8R/Rinst20c11953812158/seqcombo/examples/GVariation/A.Mont.fas"
## [2] "/tmp/RtmpP5ZN8R/Rinst20c11953812158/seqcombo/examples/GVariation/B.Oz.fas"
## [3] "/tmp/RtmpP5ZN8R/Rinst20c11953812158/seqcombo/examples/GVariation/C.Wilga5.fas"
The input fasta file should contains two aligned sequences. User need to specify which sequence (1 or 2, 1 by default) as reference. The seqdiff
function will parse the fasta file and calculate the nucleotide differences by comparing the non-reference one to reference.
## sequence differences of Mont and CF_YL21
## 1181 sites differ:
## A C G T
## 286 315 301 279
We can visualize the differences by plot
method:
We can parse several files and visualize them simultaneously.
Sequence similarity plot
Session info
Here is the output of sessionInfo()
on the system on which this document was compiled:
## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.13-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB 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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_3.3.5 emojifont_0.5.5 tibble_3.1.3 seqcombo_1.14.1
##
## loaded via a namespace (and not attached):
## [1] prettydoc_0.4.1 tidyselect_1.1.1 xfun_0.25
## [4] bslib_0.2.5.1 purrr_0.3.4 colorspace_2.0-2
## [7] vctrs_0.3.8 generics_0.1.0 htmltools_0.5.1.1
## [10] stats4_4.1.0 yaml_2.2.1 utf8_1.2.2
## [13] rlang_0.4.11 jquerylib_0.1.4 pillar_1.6.2
## [16] withr_2.4.2 glue_1.4.2 DBI_1.1.1
## [19] BiocGenerics_0.38.0 GenomeInfoDbData_1.2.6 lifecycle_1.0.0
## [22] stringr_1.4.0 zlibbioc_1.38.0 Biostrings_2.60.2
## [25] munsell_0.5.0 gtable_0.3.0 evaluate_0.14
## [28] labeling_0.4.2 knitr_1.33 IRanges_2.26.0
## [31] GenomeInfoDb_1.28.1 parallel_4.1.0 fansi_0.5.0
## [34] highr_0.9 proto_1.0.0 scales_1.1.1
## [37] showtext_0.9-4 S4Vectors_0.30.0 jsonlite_1.7.2
## [40] XVector_0.32.0 sysfonts_0.8.5 farver_2.1.0
## [43] digest_0.6.27 stringi_1.7.3 showtextdb_3.0
## [46] dplyr_1.0.7 cowplot_1.1.1 grid_4.1.0
## [49] tools_4.1.0 bitops_1.0-7 yulab.utils_0.0.2
## [52] magrittr_2.0.1 sass_0.4.0 RCurl_1.98-1.4
## [55] crayon_1.4.1 pkgconfig_2.0.3 ellipsis_0.3.2
## [58] assertthat_0.2.1 rmarkdown_2.10 R6_2.5.1
## [61] igraph_1.2.6 compiler_4.1.0
References
Chang, Fei, Fangluan Gao, Jianguo Shen, Wenchao Zou, Shuang Zhao, and Jiasui Zhan. 2015. “Complete Genome Analysis of a PVYN-Wi Recombinant Isolate from Solanum Tuberosum in China.” Potato Research 58 (4): 377–89. https://doi.org/10.1007/s11540-015-9307-3.