powertcr's Introduction

powerTCR: modeling the clone size distribution of the TCR repertoire

This is an R package for fitting the discrete gamma-GPD spliced threshold model to a distribution of clone sizes. The package contains tools needed to perform all of the analyses found in our paper, powerTCR: a model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire.

Installation

Install and load this package from BioConductor by typing in R:

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("powerTCR")

or take it directly from from GitHub with:

library(devtools)
install_github("hillarykoch/powerTCR")
library(powerTCR)

Getting going

See the package vignette for a detailed walkthrough of package features.

Citation

You may read our methods paper at PLoS Computational Biology.

If you found the powerTCR package useful, please cite our paper:

Koch H, Starenki D, Cooper SJ, Myers RM, Li Q (2018) powerTCR: A model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire. PLOS Computational Biology 14(11): e1006571. https://doi.org/10.1371/journal.pcbi.1006571

Citation for the powerTCR package is:

Koch H (2018). powerTCR: Model-Based Comparative Analysis of the TCR Repertoire. R package version 1.1.4.

powertcr's People

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powertcr's Issues

Are the Shannon Entropy and similar metrics calculated by powerTCR robust against sequencing depth?

Hi @hillarykoch,

I'm trying to compare the TCR repertoires from a bunch of samples, and the number of cells per sample vary from ~350 to ~4000. I tested powerTCR on these samples, and to my understanding this works, I understand that the distances between samples are not biased by the number of cells per sample. So, I can see that samples group the way I expected, but I also want to do a statistical test of a metric that represents something that people know what it is, such as Shannon Entropy. What I don't get is if that is sensitive to sequencing depth, or if that somehow is compensated for in your model? Could you give some advice on a suitable metric?

tcR package will soon be orphaned

Hi @hillarykoch ,

thank you for supporting the RepSeq community with your package! I would like to notify you that the tcR package will soon be orphaned in favour of our new package immunarch - https://github.com/immunomind/immunarch

I would be glad to help you move to the immunarch dependency.

What parts of tcR do you use?

Reference to the paper

Hi, I have seen you submitted the package to Bioconductor, thanks for doing so.

In the README and in the vignette there are several references to your paper. Could you provide a link or a reference to read more about the models used and the main outcomes of your analysis?

Many thanks

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hillarykoch / powertcr Goto Github PK

powertcr's Introduction

powerTCR: modeling the clone size distribution of the TCR repertoire

Installation

Getting going

Citation

powertcr's People

Contributors

Stargazers

Forkers

powertcr's Issues

Are the Shannon Entropy and similar metrics calculated by powerTCR robust against sequencing depth?

tcR package will soon be orphaned

Reference to the paper

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