Annotation
In ggmsa: Plot Multiple Sequence Alignment using 'ggplot2'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

 protein_sequences <- system.file("extdata", "sample.fasta", package = "ggmsa")
 miRNA_sequences <- system.file("extdata", "seedSample.fa", package = "ggmsa")
 nt_sequences <- system.file("extdata", "LeaderRepeat_All.fa", package = "ggmsa")

library(ggmsa)
library(ggplot2)

Annotation Introduction

For sequence annotations, ggmsa supports individual modules to annotate sequence alignments. Annotated modules can be called by a + prefix. Automatically generated annotations that containing colored labels and symbols are overlaid on MSAs to indicate potentially conserved or divergent regions.

x <- "geom_seqlogo()\tgeometric layer\tautomatically generated sequence logos for a MSA\n
geom_GC()\tannotation module\tshows GC content with bubble chart\n
geom_seed()\tannotation module\thighlights seed region on miRNA sequences\n
geom_msaBar()\tannotation module\tshows sequences conservation by a bar chart\n
geom_helix()\tannotation module\tdepicts RNA secondary structure as arc diagrams(need extra data)\n
 "
require(dplyr)
xx <- strsplit(x, "\n\n")[[1]]
y <- strsplit(xx, "\t") %>% do.call("rbind", .)
y <- as.data.frame(y, stringsAsFactors = F)

colnames(y) <- c("Annotation modules", "Type", "Description")

require(kableExtra)
knitr::kable(y, align = "l", booktabs = T, escape = T) %>% 
    kable_styling(latex_options = c("striped", "hold_position", "scale_down"))

geom_seqlogo

Protein sequence logos annotation for MSA. Sequence logos play a major role in visualizing DNA, RNA and protein binding sites. In the following example, geom_seqlogo() module is used to display sequence logos between 300 and 350 sites. The + can be used to link main function ggmsa() and geom_seqlogo() module.

ggmsa(protein_sequences, 300, 350, char_width = 0.5, seq_name = T) + 
    geom_seqlogo(color = "Chemistry_AA")

geom_GC

geom_GC() module calculating the GC-content in DNA/RNA sequences. The sizes of bubbles are identical with GC-content.

nt_sequence <- system.file("extdata", "LeaderRepeat_All.fa", package = "ggmsa")
ggmsa(nt_sequence,font = NULL, color = "Chemistry_NT") + 
    geom_seqlogo(color = "Chemistry_NT") + geom_GC() + theme(legend.position = "none")

geom_seed

geom_seed() helps to identify microRNA seed region by asterisks or shaded area. The seed region is a conserved heptameric sequence that is mostly situated at positions 2-7 from the miRNA 5´-end.

ggmsa(miRNA_sequences, char_width = 0.5, color = "Chemistry_NT") + 
    geom_seed(seed = "GAGGUAG", star = TRUE)

ggmsa(miRNA_sequences, char_width = 0.5, seq_name = T, none_bg = TRUE) + 
    geom_seed(seed = "GAGGUAG")

geom_msaBar

geom_msaBar shows the highest frequency of amino acid residues at each position by a bar chart.

ggmsa(protein_sequences, 300, 350, char_width = 0.5, seq_name = T) + geom_msaBar()

geom_helix

ggmsa supports plotting RNA secondary structure as arc diagram by reference to R4RNA. For example, adding a structure arc above diagram multiple sequence alignment helps to identify the base pair conservation and co-variation.

known_file <- system.file("extdata", "vienna.txt", package = "R4RNA")
known <- readSSfile(known_file, type = "Vienna" )
cripavirus_msa <- system.file("extdata", "Cripavirus.fasta", package = "ggmsa")

ggmsa(cripavirus_msa, font = NULL, color = "Chemistry_NT", seq_name = F, show.legend = T, border = "white") +
  geom_helix(helix_data = known)