<!-- README.md is generated from README.Rmd. Please edit that file -->
# 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
(https://doi.org/10.1371/journal.pone.0266929)](https://doi.org/10.1371/journal.pone.0266929)
**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)](https://doi.org/doi:10.18129/B9.bioc.idpr) or
## Installation
You can install the stable release version version from
[Bioconductor](https://doi.org/doi:10.18129/B9.bioc.idpr) with:
``` r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("idpr")
```
Additionally, you can install the development version from
[Bioconductor](https://bioconductor.org/packages/devel/bioc/html/idpr.html)
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](https://github.com/wmm27/idpr) 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
library(idpr)
P53_HUMAN <- TP53Sequences[2] #Getting a pre-loaded sequence from idpr
print(P53_HUMAN)
#> P04637|P53_HUMAN
#> "MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGPDEAPRMPEAAPPVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYQGSYGFRLGFLHSGTAKSVTCTYSPALNKMFCQLAKTCPVQLWVDSTPPPGTRVRAMAIYKQSQHMTEVVRRCPHHERCSDSDGLAPPQHLIRVEGNLRVEYLDDRNTFRHSVVVPYEPPEVGSDCTTIHYNYMCNSSCMGGMNRRPILTIITLEDSSGNLLGRNSFEVRVCACPGRDRRTEEENLRKKGEPHHELPPGSTKRALPNNTSSSPQPKKKPLDGEYFTLQIRGRERFEMFRELNEALELKDAQAGKEPGGSRAHSSHLKSKKGQSTSRHKKLMFKTEGPDSD"
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
)
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**Please Refer to idpr-vignette.Rmd file for a detailed introduction to
the** **idpr package.** [Link to the Vignette
(here)](https://bioconductor.org/packages/release/bioc/vignettes/idpr/inst/doc/idpr-vignette.html)
## Appendix
For use and details on ‘idpr’, see our peer-reviewed article published
in [PLOS ONE
(https://doi.org/10.1371/journal.pone.0266929)](https://doi.org/10.1371/journal.pone.0266929)
### Package citation
``` r
citation("idpr")
#>
#> To cite idpr in publications, use the citation below and other
#> function-specific sources found in the idpr package documentation:
#>
#> McFadden, W. M., and Yanowitz, J. L. (2022). idpr: A package for
#> profiling and analyzing Intrinsically Disordered Proteins in R. PLOS
#> ONE, 17(4), e0266929. doi:10.1371/journal.pone.0266929
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {idpr: A package for profiling and analyzing Intrinsically Disordered Proteins in R},
#> author = {William M McFadden and Judith L Yanowitz},
#> journal = {PLOS ONE},
#> publisher = {Public Library of Science},
#> year = {2022},
#> volume = {17},
#> number = {4},
#> pages = {e0266929},
#> doi = {10.1371/journal.pone.0266929},
#> url = {https://bioconductor.org/packages/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,
<https://doi.org/10.1093/nar/gky384>
- Erdős, G., & Dosztányi, Z. (2020). Analyzing protein disorder with
IUPred2A. Current Protocols in Bioinformatics, 70, e99.
<https://doi.org/10.1002/cpbi.99>
- Kozlowski, L. P. (2016). IPC – Isoelectric Point Calculator. Biology
Direct, 11(1), 55. <https://doi.org/10.1186/s13062-016-0159-9>
- 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. <https://doi.org/10.1080/21690707.2015.1135015>
- 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.
<https://doi.org/10.1002/1097-0134(20001115)41:3>\<415::AID-PROT130\>3.0.CO;2-7
### Additional Information
``` r
Sys.time()
#> [1] "2022-04-25 12:20:36 EDT"
Sys.Date()
#> [1] "2022-04-25"
R.version
#> _
#> platform x86_64-apple-darwin17.0
#> arch x86_64
#> os darwin17.0
#> system x86_64, darwin17.0
#> status
#> major 4
#> minor 1.3
#> year 2022
#> month 03
#> day 10
#> svn rev 81868
#> language R
#> version.string R version 4.1.3 (2022-03-10)
#> nickname One Push-Up
```
