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] "/private/tmp/RtmpTHd6JZ/Rinst15d064abe3f71/seqcombo/examples/GVariation/A.Mont.fas"  
## [2] "/private/tmp/RtmpTHd6JZ/Rinst15d064abe3f71/seqcombo/examples/GVariation/B.Oz.fas"    
## [3] "/private/tmp/RtmpTHd6JZ/Rinst15d064abe3f71/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.

x1 <- seqdiff(fas[1], reference=1)
x1
## 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:

plot(x1)

We can parse several files and visualize them simultaneously.

x <- lapply(fas, seqdiff)
plts <- lapply(x, plot)
plot_grid(plotlist=plts, ncol=1, labels=LETTERS[1:3])

Sequence similarity plot

fas <- system.file("examples/GVariation/sample_alignment.fa", package="seqcombo")
simplot(fas, 'CF_YL21')

Session info

Here is the output of sessionInfo() on the system on which this document was compiled:

## R version 4.0.0 (2020-04-24)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Mojave 10.14.6
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] igraph_1.2.5    ggplot2_3.3.0   emojifont_0.5.3 tibble_3.0.1   
## [5] seqcombo_1.10.0
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.4.6        BiocManager_1.30.10 compiler_4.0.0     
##  [4] pillar_1.4.3        XVector_0.28.0      sysfonts_0.8       
##  [7] prettydoc_0.3.1     tools_4.0.0         zlibbioc_1.34.0    
## [10] digest_0.6.25       evaluate_0.14       lifecycle_0.2.0    
## [13] gtable_0.3.0        pkgconfig_2.0.3     rlang_0.4.5        
## [16] rvcheck_0.1.8       yaml_2.2.1          parallel_4.0.0     
## [19] xfun_0.13           proto_1.0.0         withr_2.2.0        
## [22] showtextdb_2.0      stringr_1.4.0       dplyr_0.8.5        
## [25] knitr_1.28          Biostrings_2.56.0   S4Vectors_0.26.0   
## [28] vctrs_0.2.4         IRanges_2.22.0      tidyselect_1.0.0   
## [31] stats4_4.0.0        grid_4.0.0          cowplot_1.0.0      
## [34] glue_1.4.0          R6_2.4.1            rmarkdown_2.1      
## [37] farver_2.0.3        purrr_0.3.4         magrittr_1.5       
## [40] scales_1.1.0        htmltools_0.4.0     ellipsis_0.3.0     
## [43] BiocGenerics_0.34.0 showtext_0.7-1      assertthat_0.2.1   
## [46] colorspace_1.4-1    labeling_0.3        stringi_1.4.6      
## [49] munsell_0.5.0       crayon_1.3.4

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.