The goal of rsrm is to generate the distribution of Restriction Sites on given DNA sequence and also construct the Restriction Map with given single and double digests reaction result.

You can install the development version from GitHub with:

# install.packages("devtools")
require("devtools")
install_github("LoadingBFX/rsrm", build_vignettes = TRUE)
library("rsrm")

To run the shinyApp:

runRsrmApp()

browseVignettes("rsrm")

• rsrm stands for Restriction Site and Restriction Map. The package contains 2 functions will help you to generate the distribution of RS on given DNA sequence and also construct the RM with given single and double digests reaction result. Also there is a shinyApp for function findre(), run the Shiny app by

runRsrmApp()

• First function of rsrm package is RS. Locating the restriction sites around target sequnce.

  • findre() will find all of the positions can be cut by the enzymes in dataset. You can set the number of enzymes to display in the plot. Default value is 6, which means 6 enzymes will be displayed on the plot for both side of target sequence (totally 12 sites, 6 for left, 6 for right, 1 for target, if there are enough sites.). example:

    seq1 <- 'GGCAGATTCCCCCTAACGTCGGACCCGCCCGCACCATGGTCAGGCATGCCCCTCCTCATCGCTGGGCACAGCCCAGAGGGT
    ATAAACAGTGCTGGAGGCTGGCGGGGCAGGCCAGCTGAGTCCTGAGCAGCAGCCCAGCGCAGCCACCGAGACACC
    ATGAGAGCCCTCACACTCCTCGCCCTATTGGCCCTGGCCGCACTTTGCATCGCTGGCCAGGCAGGTGAGTGCCCC'
    name1 <- 'Example gene for test findre (EGFTF)'
    seq2 <- 'ACGTCG'
    name2 <- 'Target'
    result <- findre(name1, seq1, name2, seq2)
    result

    

• Second function is to construct RM for unknown sequence which is also useful for DNA Sequencing.

  • Everyone who took BCH Course must has see this kind of question on exam

    Unknown sequence and fragment obtained in single and double digests reaction were:
    EcoRI: 70, 30kb
    HaeIII: 60, 40kb
    EcoRI + HaeIII: 40, 30, 20, 10kb
    Q: construct a restriction map of unknown sequence.
    

    Now you can easily put single and double digests reaction result in rsmap() function to construct thr RM for you

    frag1 <- c(70, 30)
    frag2 <- c(60, 40)
    dou_dig <- c(40, 30, 20, 10)
    enz1 <- "EcoRI"
    enz2 <- "HaeIII"
    rsmap(enz1, frag1, enz2, frag2, dou_dig)

    

library("rsrm")
lsf.str("package:rsrm")

The author of the package is Fanxing Bu. sanitizeSeq() is adapted from Dr. Steipe’s function dbSanitizeSequence() in course BCH441 ABC-units. It has been indicated and referenced in the utility.R file. The rest functions were authored by Fanxing.

Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models The R Journal 8/1, pp. 205-233 https://cran.r-project.org/web/packages/mclust/vignettes/mclust.html

Boris Steipe BCH441 - Bioinformatics http://steipe.biochemistry.utoronto.ca/abc/index.php/Bioinformatics_Main_Page

This package was developed as part of an assessment for 2019 BCB410H: Applied Bioinformatics, University of Toronto, Toronto, CANADA.