معرفی شرکت ها
TCRcloud-1.3.1
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مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
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مشاهده بیشتر
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مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
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مشاهده بیشترتوضیحات
TCRcloud is a TCR repertoire visualization and comparison tool
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | TCRcloud-1.3.1 |
| نام | TCRcloud |
| نسخه کتابخانه | 1.3.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Eric de Sousa |
| ایمیل نویسنده | eric.desousa@research.fchampalimaud.org |
| آدرس صفحه اصلی | https://github.com/eriicdesousa/TCRcloud |
| آدرس اینترنتی | https://pypi.org/project/TCRcloud/ |
| مجوز | - |
## TCRcloud is a TCR repertoire visualization and comparison tool
**Instalation**
TCRcloud is written in python and can be installed from PyPI using pip:
pip3 install TCRcloud
Currently it is only compatible with Linux (x86-64) and macOS (x86-64) because one of the dependencies used is also only compatible with those operating systems. It does work on WSL if you want to use Windows.
TCRcloud uses the AIRR Data Commons API and needs AIRR compliant data as input.
TCRcloud was initially developed for TCR repertoires but it is also compatible with BCR repertoires.
**Usage**
**To create a word cloud**
TCRcloud cloud repertoire.airr.rearrangements.tsv
By default TCRcloud colours the CDR3 based on the Vgene but you can provide a json file that atributes colours in Hex format to specific sequences:
{
"#FF0000":["CAASITGNQFYF","CAVREDGTSGSARQLTF"],
"#0000FF":["CAVMDSNYQLIW"]
}
The sequences not in the file will be coloured grey.
Only the colours for human TCR and BCR variable genes are coded into TCRcloud.
**To use your custom colours for the word cloud**
TCRcloud cloud repertoire.airr.rearrangements.tsv -c colours.json
**To create a word cloud without a legend**
TCRcloud cloud repertoire.airr.rearrangements.tsv -l False
**To create a radar plot comparing diversity metrics**
TCRcloud radar repertoire.airr.rearrangements.tsv
By default TCRcloud uses repertoire_id but you can create a legend with the text you want by providing a json file:
{
"2839362682105696746-242ac113-0001-012":"Twin 2A",
"2939134772391776746-242ac113-0001-012":"Twin 2B"
}
**To create a radar plot with your desired legend**
TCRcloud radar repertoire.airr.rearrangements.tsv -c legend.json
**To create a radar plot without a legend**
TCRcloud radar repertoire.airr.rearrangements.tsv -l False
**To export the calculated metrics from the radar to a text file**
TCRcloud radar repertoire.airr.rearrangements.tsv -e True
**The metrics utilized in the radar**
**Distinct CDR3:** A simple count of the unique CDR3 sequences in the sample
**D50 Index:** Developed by Dr Jian Han, this metric represents the percent of dominant and unique T or B cell clones that account for the cumulative 50% of the total CDR3 counted in the sample
**Convergence:** Frequency of CDR3 amino acid sequences that are coded by more than one nucleotide sequence
**Gini Index:** Originally developed by Dr Corrado Gini to represent the wealth inequality within a social group, this metric is a measure of distribution, with 0 representing perfect equality and 1 representing perfect inequality between CDR3
**Shannon Index:** Originally developed by Dr Claude Shannon to quantify the entropy in strings of text, this metric takes into account the number of CDR3 present, as well as, the relative abundance of each CDR3 and higher the number, the higher is the species diversity
**Simpson Index:** Originally developed by Dr Edward H. Simpson to measure diversity in a ecosystem, this metric measures the probability that two randomly selected CDR3 are different
**Chao1 index:** Originally developed by Dr Anne Chao to estimate richness in a community, this metric indicates the estimated number of CDR3 in a sample
Using TCRcloud you can download rearragements files from the AIRR compliant databases based on AIRR repertoire metadata files
**To download AIRR rearrangements files**
TCRcloud download repertoire.airr.json
TCRcloud provides some test data to experiment the tool. The data is one twin pair from the monozygotic twins study from the Mark Davis lab (DOI:[ 10.1038/ncomms11112](https://doi.org/10.1038/ncomms11112))
**To download the test data repertoire file**
TCRcloud testdata
After having the testdata.airr.json file you can use the download function included in TCRcloud to get the matching rearragements file.
## Examples:
**TRA CDR3 word cloud**
**TRB CDR3 word cloud**
**TRG CDR3 word cloud**
**TRD CDR3 word cloud**
**Diversity comparison**
Comparing here the αβ repertoire from one twin pair from the monozygotic twins study from the Mark Davis lab (DOI:[10.1038/ncomms11112](https://doi.org/10.1038/ncomms11112))
نیازمندی
| مقدار | نام |
|---|---|
| - | airr |
| >=1.9.2 | numpy |
| <=1.8.1,>=1.3.0 | scipy |
| - | matplotlib |
| - | wordcloud |
| - | pandas |
| - | scikit-learn |
| - | scikit-bio |
| - | requests |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl TCRcloud-1.3.1:
pip install TCRcloud-1.3.1.whl
نصب پکیج tar.gz TCRcloud-1.3.1:
pip install TCRcloud-1.3.1.tar.gz