In helen307/phyMSAViewer: Provide Phylogenetic tree and MSA visualization from Uniprot IDs

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Introduction

phyMSAViewer is a helpful tool that enables users to have a general overview on multiple selected sequences. It also provides multiple sequence alignment on the side and enables users to zoom on a particular range of the multiple sequence alignment to have a better view of the amino acids. Function uniprotToPhy enables users to view the phylogenetic tree with the multiple sequence alignment by entering Uniprot IDs. Function seqToPhy enables users to view the phylogenetic tree with the multiple sequence alignment by providing a fasta file containg the selected sequences. Function uniprotToFasta enables users to retrieve fasta file that contains sequences of interest by entering Uniprot IDs. The shiny implementation of phyMSAViewer is available as a Shiny App (indicated below). For more information, see details below. This document gives a tour of phyMSAViewer functionalities. It was written in Rmarkdown, using the knitr package for production.

See help(package=phyMSAViewer) for further details and references provided by citation("phyMSAViewer"). To download phyMSAViewer, use the following commands:

library(devtools)
devtools::install_github("helen307/phyMSAViewer", build_vignettes=TRUE)
library(phyMSAViewer)

To run the Shiny App:

shiny::runApp(appDir = system.file("phyMSAViewerShinyApp", package = "phyMSAViewer"),)

To list all functions available in the package:

lsf.str("package:phyMSAViewer")

MSA algorithm

Normally building a phylogenetic tree starts from providing with a sequence fasta file. In this package, we allow users to start by typing in the Uniprot IDs. Then we download the sequence data from Swiss-Prot. The reason why we chose to perform MSA (multiple sequence alignment) using the algorithm MUSCLE is because ClusterW implements an interative method. Therefore, the calculation errors will be accumulated. MUSCLE has a progressive algorithm that optimizes at each step. Here is an image that explains the alogrithm of MUSCLE in detail:

Creation of phylogenetic trees

We used the neighbor-joining (NJ) algorithm to create our phylogenetic tree after we obtain the pairwise distances from the sequences. This algorithm joins the two closest sub-trees that are not already joined. A "neighbor" is defined as two texa that are connected by a single node in an unrooted tree. Here is an image showing how the NJ algorithm perform its greedy actions:

Example

1. uniprotToPhy: We will expect the users to enter a list of Uniprot IDs separated by "OR"s, and the function will return a phylogenetic tree with multiple sequence alignment on the side.

library(phyMSAViewer)
phyMSA <- uniprotToPhy(ID="AC=P19838 OR AC=Q00653 OR AC=Q01201")
# Access the phylogenetic tree with MSA plot directly from the object.
phyMSA

1. seqToPhy: We will expect the users to provide a AAStringSet instance sequence file (read from a fasta file). You can make this file by:

# mySeqs <- Biostrings::readAAStringSet("<Your fasta file name>.fasta")
seqPhyMSA <- seqToPhy(mySeqs) # mySeqs is a dataset in this package
# Access the phylogenetic tree with MSA plot directly from the object.
seqPhyMSA

1. uniprotToFasta: We will create a fasta file of sequences from the user entered Uniprot IDs.

# Use the following UniprotID for this function: P19838, Q00653, Q01201
phyMSAViewer::uniprotToFasta("AC=P19838 OR AC=Q00653 OR AC=Q01201")

# A file called seqs.fasta will appear in the main directory.

References

1. Charif, D., Lobry, J. R., Necsulea, A., Palmeira, L., Penel, S., Perriere, G., & Penel, M. S. (2020). Package ‘seqinr’.
2. Edgar, R. C. (2004). MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic acids research, 32(5), 1792-1797.
3. Simonsen, M., Mailund, T., & Pedersen, C. N. (2008, September). Rapid neighbour-joining. In International Workshop on Algorithms in Bioinformatics (pp. 113-122). Springer, Berlin, Heidelberg.
4. UniProt Consortium. (2015). UniProt: a hub for protein information. Nucleic acids research, 43(D1), D204-D212.
5. Wickham, H., Danenberg, P., & Eugster, M. (2017). roxygen2: in-line documentation for R. R package version, 6(1).
6. Wickham, H., & Bryan, J. (2018). Usethis: Automate package and project setup.
7. Wickham, H., Hester, J., Chang, W., & Hester, M. J. (2020). Package ‘devtools’.
8. Xie, Y. (2014). knitr: a comprehensive tool for reproducible research in R. Implement Reprod Res, 1, 20.
9. Yu, G., Smith, D. K., Zhu, H., Guan, Y., & Lam, T. T. Y. (2017). ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution, 8(1), 28-36.

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helen307/phyMSAViewer documentation built on Jan. 1, 2021, 3:16 a.m.