Sequence difference plot

Here we use the data published in Potato Research(Chang et al. 2015) as an example.

## [1] "/tmp/RtmpX4M2lG/Rinst629561a4f474/seqcombo/examples/GVariation/A.Mont.fas"  
## [2] "/tmp/RtmpX4M2lG/Rinst629561a4f474/seqcombo/examples/GVariation/B.Oz.fas"    
## [3] "/tmp/RtmpX4M2lG/Rinst629561a4f474/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 4.0.0 RC (2020-04-19 r78255)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.12-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.12-bioc/R/lib/libRlapack.so
## 
## 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] 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_1.11.0
## 
## 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_0.29.0      sysfonts_0.8       
##  [7] prettydoc_0.3.1     tools_4.0.0         zlibbioc_1.35.0    
## [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_2.57.0   S4Vectors_0.27.0   
## [28] vctrs_0.2.4         IRanges_2.23.0      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_0.35.0 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.