# scRepertoire
#### A toolkit for single-cell immune profiling
<img align="right" src="https://github.com/ncborcherding/ncborcherding.github.io/blob/master/images/hex_sticker_v2.png" width="305" height="352">
### Introduction
Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine RNA and immune profiling, scRepertoire was built to process data derived from the 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with the popular Seurat R package.
### Wrapper Functions
scRepertoire v1.0.2 has the functionality of the [powerTCR](https://github.com/hillarykoch/powerTCR) approach to comparing clone size distribution, [please cite](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006571) the manuscript if using the ```clonesizeDistribution()``` function. In addition, we recently added the [Startrac](https://github.com/Japrin/STARTRAC) clonotype metrics, if using the ```StartracDiversity()``` please read and cite [the accompanying article](https://www.nature.com/articles/s41586-018-0694-x).
### Installation
```
devtools::install_github("ncborcherding/scRepertoire")
```
#### Most up-to-date version
We are working on constantly improving the scRepertoire package - these improvements can be found under the "dev" branch. These changes will be incorporated into the main branch as they are tested more throughly.
```
devtools::install_github("ncborcherding/scRepertoire@dev")
```
#### Bioconductor
[scRepertoire](https://www.bioconductor.org/packages/release/bioc/html/scRepertoire.html) is now on Bioconductor. Use the link to find out more information. scRepertoire (for R v4 or greater) can be installed from Bioconductor with:
```
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scRepertoire")
```
### Getting Data
Unfortunately, Github limits the size of individual files. In order to access the seurat object paired with scRepetoire please download the .rda from [here](https://drive.google.com/open?id=1np-EzG7U9W_Fz_SchBrsAhtqE3_rB_H9).
### Learning To Use scRepertoire
Vignette available [here](https://ncborcherding.github.io/vignettes/vignette.html), includes almost 13,000 T cells across 3 patients with renal clear cell carcinoma.
### Please Cite
Feel free to use, edit, modify scRepertoire, but if you do, please cite the [manuscript](https://f1000research.com/articles/9-47/v1).
### Contact
Questions, comments, suggestions, please feel free to contact Nick Borcherding via this repository, [email](mailto:ncborch@gmail.com), or using [twitter](https://twitter.com/theHumanBorch).
### More Information On VDJ Biology
Our publication is limited in scope and size and we were unable to review VDJ biology and issues relevant to high-throuhput immune receptor profiling. If you are interested in the biology of the process, please refer to the excellent reviews from [Jahong Ji](https://www.nature.com/articles/nri2941) and [Frederick Alt](https://www.cell.com/fulltext/S0092-8674(04)00039-X). Additionally, the complexities of sequencing and quantifications of VDJs are discussed [here.](https://www.nature.com/articles/nprot.2018.021?)
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scRepertoire:单细胞免疫分析的工具包
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曲目 单细胞免疫分析的工具包 介绍 单细胞测序是免疫学和肿瘤学领域的一项新兴技术,它使研究人员能够将RNA定量和其他方式耦合在一起,例如在单个细胞水平上对免疫细胞受体进行谱分析。 已经创建了许多工作流程和软件包来处理和分析单细胞转录组数据。 这些程序包使用户可以利用在基于单细胞的实验中生成的数据的广阔维度,并将数据提炼成新颖的见解。 与转录组领域不同,缺少允许单细胞免疫受体分析的软件选项。 为了使用户能够轻松地将RNA和免疫分布图结合起来,scRepertoire能够处理从10倍基因组学Chrome免疫分布图获得的T细胞受体(TCR)和免疫球蛋白(Ig)富集工作流程的数据,然后与流行的Seurat R软件包进行交互。 包装功能 scRepertoire v1.0.2具有方法的功能来比较克隆大小分布,如果使用clonesizeDistribution()函数, 该手稿。 此外,我们最近添加了
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scRepertoire-master.zip (59个子文件)
scRepertoire-master
vignettes
vignette.Rmd 25KB
NAMESPACE 2KB
DESCRIPTION 1KB
R
combineContigs.R 11KB
startrac.R 26KB
seuratFunctions.R 12KB
viz.R 21KB
diversity.R 3KB
overlap.R 3KB
processing.R 8KB
clonalProportion.R 3KB
global.R 1KB
contig_list.R 143B
clonalHomeostasis.R 3KB
screp_example.R 148B
utils.R 16KB
.Rbuildignore 38B
README.md 4KB
NEWS 4KB
data
contig_list.rda 683KB
screp_example.rda 2.96MB
man
getCirclize.Rd 1KB
stripBarcode.Rd 843B
vizVgenes.Rd 1KB
clonesizeDistribution.Rd 1KB
clonalDiversity.Rd 1KB
highlightClonotypes.Rd 1KB
Startrac.Rd 2KB
lengthContig.Rd 2KB
show.Rd 371B
getSig.Rd 654B
combineTCR.Rd 2KB
StartracDiversity.Rd 1KB
subsetContig.Rd 1KB
clonalHomeostasis.Rd 1KB
pIndex.Rd 681B
occupiedscRepertoire.Rd 2KB
show-StartracOut-method.Rd 366B
Startrac.run.Rd 963B
screp_example.Rd 358B
combineBCR.Rd 2KB
StartracOut.Rd 1KB
alluvialClonotypes.Rd 2KB
quantContig.Rd 1KB
mrow.entropy.Rd 333B
initialize-methods.Rd 774B
clonalOverlap.Rd 2KB
abundanceContig.Rd 2KB
addVariable.Rd 1KB
expression2List.Rd 1KB
compareClonotypes.Rd 2KB
initialize-StartracOut-method.Rd 496B
combineExpression.Rd 2KB
clonalProportion.Rd 1KB
calIndex.Rd 833B
mcol.entropy.Rd 342B
contig_list.Rd 350B
loginfo.Rd 338B
.gitignore 22B
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