immunarch-shiny is a simple application allowing user to upload their data and immediately get plots for various immune repertoires features. Currently only diversity estimation is available.
- Make possible analysis of immune repertoires without R knowledge
- Speed up the process of scientific insights generation
heatmap3 (>= 1.1.6),
ggrepel (>= 0.8.0),
reshape2 (>= 1.4.2),
factoextra (>= 1.0.4),
fpc,
circlize,
MASS (>= 7.3),
Rtsne (>= 0.15),
readr (>= 1.3.1),
readxl (>= 1.3.1),
shiny (>= 1.4.0),
shinythemes,
treemap,
airr,
ggseqlogo,
UpSetR (>= 1.4.0),
stringr (>= 1.4.0),
ggalluvial (>= 0.10.0),
Rcpp (>= 1.0),
magrittr,
tibble (>= 2.0),
methods,
scales,
ggpubr (>= 0.2),
rlang (>= 0.4),
plyr,
dbplyr (>= 1.4.0)
R (>= 3.5.0),
ggplot2 (>= 3.1.0),
dplyr (>= 0.8.0),
dtplyr (>= 1.0.0),
data.table (>= 1.12.6),
gridExtra (>= 2.2.1),
immunarch (>= 0.5.5)
knitr (>= 1.8),
roxygen2 (>= 3.0.0),
testthat (>= 2.1.0),
pkgdown (>= 0.1.0),
assertthat,
sparklyr (>= 1.0)
Launch Shiny app from terminal:
R -e "shiny::runApp('path/to/shiny/app')"
Then go connect to app in browser navigating to address and port from terminal.
Alternatively, you can open application code in R Studio and launch by Run App button.
- Basic example, showing diversity between all samples in test dataset, estimated using Chao1.
- Samples grouped by sex and status:
- R programming language (https://r-project.org/)
- Shiny framework (https://shiny.rstudio.com/)
- Mastering Shiny, tutorial under early development (https://mastering-shiny.org)
immunarchpackage for immune data analysis (https://immunarch.com/)- Miho, E., Yermanos, A., Weber, C.R., Berger, C.T., Reddy, S.T. and Greiff, V., 2018. Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires. Frontiers in immunology, 9, p.224.
Shamil Urazbakhtin - shamil.utaraptor@gmail.com