TCRconvertR

Convert TCR gene names

https://github.com/seshadrilab/tcrconvertr

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Repository

Convert TCR gene names

Basic Info

Host: GitHub
Owner: seshadrilab
License: other
Language: R
Default Branch: main
Homepage: https://seshadrilab.github.io/tcrconvertr/
Size: 3.52 MB

Statistics

Stars: 4
Watchers: 3
Forks: 0
Open Issues: 7
Releases: 0

Created over 1 year ago · Last pushed about 1 year ago

Metadata Files

Readme Changelog License

README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```


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# Convert TCR gene names

`TCRconvertR` converts V, D, J, and/or C gene names between the 10X Genomics, Adaptive Biotechnologies, and IMGT nomenclatures. IMGT is the AIRR Community–recommended standard. It supports alpha-beta and gamma-delta T cell receptors (TCRs) for human, mouse, and rhesus macaque. Users can also define custom species, see: `vignette("custom-species")`. A [Python version](https://github.com/seshadrilab/tcrconvert) with command-line support is also available.

## Background

TCR annotation tools use different gene naming conventions, making cross-dataset searches difficult (e.g., identifying 10X-annotated TCRs in Adaptive data). Manual conversion is complex and error-prone due to inconsistencies in naming rules.

`TCRconvertR` automates this process efficiently and accurately. Our approach is based on analyzing multiple 10X and Adaptive data sets to capture their naming variations.

## Installation

Install the latest stable version from [CRAN](https://cran.r-project.org/web/packages/TCRconvertR/index.html):

```r
install.packages("TCRconvertR")
```

You can also install the development version from GitHub:

```r
# install.packages("pak")
pak::pak("seshadrilab/tcrconvertr")
```

## Usage

#### 1. Load TCRs into a data frame

Examples of files you may want to load:

- **10X**: `filtered_contig_annotations.csv`
- **Adaptive**: `Sample_TCRB.tsv`
- **IMGT**: Output from `MiXCR` or other tools

```{r}
library(TCRconvertR)

tcr_file <- get_example_path("tenx.csv") # Using built-in example file
tcrs <- read.csv(tcr_file)[c("barcode", "v_gene", "j_gene", "cdr3")]
tcrs
```

####  2. Convert

```{r}
new_tcrs <- convert_gene(tcrs, frm = "tenx", to = "adaptive")
new_tcrs
```

## Contributing

Contributions are welcome! To contribute, submit a pull request. See the documentation for details.

## Issues

To report a bug or request a feature please open an 
[issue](https://github.com/seshadrilab/tcrconvertr/issues).

## Contact

For other inquiries, contact Emma Bishop: emmab5 at uw dot edu.

## Acknowledgments

This project was supported by the Fred Hutchinson Cancer Center Translational Data Science Integrated Research Center (TDS IRC) through the 2024 Data Scientist Collaboration Grant. Special thanks to Scott Chamberlain for development support and Shashidhar Ravishankar for gene name curation.

Owner

Name: seshadrilab
Login: seshadrilab
Kind: organization

Repositories: 4
Profile: https://github.com/seshadrilab

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Last Year

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Total issues: 19
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Average time to close issues: 28 days
Average time to close pull requests: 8 days
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Average comments per issue: 0.42
Average comments per pull request: 2.0
Merged pull requests: 7
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Past Year

Issues: 19
Pull requests: 7
Average time to close issues: 28 days
Average time to close pull requests: 8 days
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Average comments per issue: 0.42
Average comments per pull request: 2.0
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Top Authors

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emjbishop (18)
sckott (1)

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emjbishop (6)

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enhancement (9) bug (1)

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Packages

Total packages: 1
Total downloads:
- cran 365 last-month

Total dependent packages: 0
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Total versions: 1
Total maintainers: 1

cran.r-project.org: TCRconvertR

Convert TCR Gene Names

Homepage: https://github.com/seshadrilab/tcrconvertr
Documentation: http://cran.r-project.org/web/packages/TCRconvertR/TCRconvertR.pdf
License: MIT + file LICENSE
Latest release: 1.0
published about 1 year ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 365 Last month

Rankings

Dependent packages count: 26.7%

Dependent repos count: 32.9%

Average: 48.8%

Downloads: 86.7%

Maintainers (1)

emmab5@uw.edu