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--- output: github_document --- <!-- is generated from README.Rmd. Please edit that file --> ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "75%" ) ``` # idpr Overall, ‘idpr’ aims to integrate tools for the computational analysis of intrinsically disordered proteins within R. This package is used to identify known characteristics of IDPs within a sequence of interest with easily reported and dynamic results. Additionally, this package also includes tools for IDP-based sequence analysis to be used in conjunction with other R packages. See our recently published peer-reviewed publication in [PLOS ONE (]( **Please Refer to idpr-vignette.Rmd file for a detailed introduction to the** **idpr package.** Links to the vignettes found at the [Bioconductor landing page (here)]( or ## Installation You can install the stable release version version from [Bioconductor]( with: ```r if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("idpr") ``` Additionally, you can install the development version from [Bioconductor]( with: ``` r if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") # The following initializes usage of Bioc devel BiocManager::install(version='devel') ``` Or you can install the most recent development version from [GitHub]( with: ``` r # install.packages("devtools") #if not already installed devtools::install_github("wmm27/idpr") ``` ## Example This is a basic example to quickly profile your protein of interest: ```{r example} library(idpr) P53_HUMAN <- TP53Sequences[2] #Getting a pre-loaded sequence from idpr print(P53_HUMAN) P53_ID <- "P04637" #Human TP53 UniProt ID #Generates the IDP Profile: idprofile(sequence = P53_HUMAN, uniprotAccession = P53_ID, proteinName = "TP53 Human", #Optional Argument window = 11, #Optional Argument pKaSet = "Lehninger", #Optional Argument iupredType = "redox" #Optional Argument ) ``` **Please Refer to idpr-vignette.Rmd file for a detailed introduction to the** **idpr package.** [Link to the Vignette (here)]( ## Appendix For use and details on 'idpr', see our peer-reviewed article published in [PLOS ONE (]( ### Package citation ```{r} citation("idpr") ``` ### Function citations * Bálint Mészáros, Gábor Erdős, Zsuzsanna Dosztányi, IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding, Nucleic Acids Research, Volume 46, Issue W1, 2 July 2018, Pages W329–W337, * Erdős, G., & Dosztányi, Z. (2020). Analyzing protein disorder with IUPred2A. Current Protocols in Bioinformatics, 70, e99. * Kozlowski, L. P. (2016). IPC – Isoelectric Point Calculator. Biology Direct, 11(1), 55. * Kyte, J., & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. Journal of molecular biology, 157(1), 105-132. * Nelson, D. L., & Cox, M. M. (2017). Lehninger Principles of Biochemistry (Seventh ed.). New York, NY: W. H. Freeman and Company. * Prilusky, J., Felder, C. E., et al. (2005). FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics, 21(16), 3435-3438. * Uversky, V. N. (2016). Paradoxes and wonders of intrinsic disorder: Complexity of simplicity. Intrinsically Disordered Proteins, 4(1), e1135015. * Uversky, V. N. (2013). A decade and a half of protein intrinsic disorder: Biology still waits for physics. Protein Science, 22(6), 693-724. doi:10.1002/pro.2261 * Uversky, V. N., Gillespie, J. R., & Fink, A. L. (2000). Why are “natively unfolded” proteins unstructured under physiologic conditions?. Proteins: structure, function, and bioinformatics, 41(3), 415-427.<415::AID-PROT130>3.0.CO;2-7 ### Additional Information ```{r} Sys.time() Sys.Date() R.version ```