barcodetrackR: an R package and app for tracking cellular barcode experiments.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
inst/barcode_app
man
.Rbuildignore
.gitignore
DESCRIPTION
NAMESPACE
README.md
barcodetrackR.Rproj

README.md

barcodetrackR

This is an R package originally built for the use of cellular barcoding experiments performed at the Dunbar Lab at the National Institutes of Health. It includes a Shiny app for ease of use.

Code by Diego A. Espinoza and Samson J. Koelle.

Installation

To install this package, try the following commands in R:

install.packages("devtools") #or skip, if you already have it
devtools::install_github("d93espinoza/barcodetrackR") #installs package from GitHub

Running the app

After installation, use the following code to run the associated app:

barcodetrackR::launchApp()

Outfile must a tab-delimited .txt with barcodes as rows, samples as column headers and reads populating the sample matrix. Below is the needed format:

File 1 File 2 File 3 File 4 ...
Barcode 1 1000 934 955 20 ...
Barcode 2 450 90004 0 0 ...
Barcode 3 300 5001 95 100000 ...
... ... ... ... ... ...

Keyfile must be a tab-delimited .txt file that must include the columns "FILENAME" and "GIVENNAME" as so (may include other columns):

FILENAME GIVENNAME
File 1 Sample name 1
File 2 Sample name 2
File 3 Sample name 3
File 4 Sample name 4
... ...

The optional README must be a tab-delmited .txt. Lines may be commented out anywhere on the .txt and will not be read. The README needs to have a FILENAME, MAPPED, and READS column. Below is the example format:

FILENAME MAPPED READS ...
File 1 3000456 4000000 ...
File 2 500000 3500000
File 3 100893 400000 ...
... ... ... ...

Included Functions

The following R functions are included in this package:

barcodecount()
#counts the number of barcodes across samples (unique, cumulative, new)

BBHM()
#shows the emergence of barcodes over time in a heatmap

barcode_ggheatmap()
#displays heatmap of the top N clones in selected samples

clonaldiversity()
#calcuate diversity indices for samples across time

cor_plot()
#wrapper for corrplot from corrplot package, with normalizations for barcode data

diversity_plotter()
#plot the diversity of samples across time

gettopindices()
#extracts the top N indices for a data frame per column, eliminating repeats

launchApp()
#launch the shiny app that eases the use of the majority these functions

merger()
#merges list of matrices by rowname, including all entries

radartopclones()
#radar plot of top N clones in a sample across samples

richness_plotter()
#plots the barcode counts of samples across time

threshold()
#eliminates barcodes that aren't present X times in at least one sample

treemap()
#tree map of a given sample