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# 1. 从GitHub下载安装CIRI-deep环境
# 论文
CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning
https://onlinelibrary.wiley.com/doi/10.1002/advs.202308115
# 模型结构
CIRI-deep模型可有效用于各转录组样本间推断差异剪接环形RNA,拓展了环形RNA的研究范围,为环形RNA研究提供了新的高效分析方法。同时,CIRI-deepA模型可以提供单细胞及空间水平环形RNA的有效解析,
![img](./images/image.png)
# 算法原理
CIRI deep通过深度神经网络对circRNA的顺式特征和样本对(总RNA或富含poly(A)的RNA)的RBP表达进行训练。
![Alt text](./images/image-1.png)
# 环境配置
## Docker(方法一)
``` ```
git clone https://github.com/gyjames/CIRIdeep.git docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
docker run -dit --shm-size 80g --network=host --name=CIRI --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /opt/hyhal/:/opt/hyhal/:ro image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10 /bin/bash
docker exec -it CIRI /bin/bash
```
安装依赖
```
pip install ./whl/tensorflow-1.15.1+git06e2e8aa.dtk2404-cp37-cp37m-linux_x86_64.whl
pip install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com
```
## Dockerfile(方法二)
```
docker build -t geneformer:latest .
docker run -dit --shm-size 80g --network=host --name=geneformer --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /opt/hyhal/:/opt/hyhal/:ro geneformer:latest /bin/bash
docker exec -it CIRI /bin/bash
```
## anaconda
1.创建conda虚拟环境:
```
conda create -n CIRI python=3.7
conda activate CIRI
```
2.其它依赖库参照requirements.txt安装:
``` ```
# 安装环境 pip install ./whl/tensorflow-1.15.1+git06e2e8aa.dtk2404-cp37-cp37m-linux_x86_64.whl
pip install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com
``` ```
conda create -n CIRIdeep python=3.7
source activate CIRIdeep
pip install tensorflow-1.15.1+git06e2e8aa.dtk2404-cp37-cp37m-linux_x86_64.whl # 预测
pip install -r requirements.txt
pip install 'h5py<3.0.0'
pip install protobuf==3.20.1 -i https://pypi.tuna.tsinghua.edu.cn/simple
```
环境安装包如下:
```
absl-py 2.1.0
astor 0.8.1
certifi 2022.12.7
cycler 0.11.0
gast 0.2.2
google-pasta 0.2.0
grpcio 1.62.3
h5py 2.10.0
importlib-metadata 6.7.0
joblib 1.3.2
Keras 2.3.1
Keras-Applications 1.0.8
Keras-Preprocessing 1.1.2
kiwisolver 1.4.5
Markdown 3.4.4
MarkupSafe 2.1.5
matplotlib 3.3.4
numpy 1.19.2
opt-einsum 3.3.0
pandas 1.1.5
Pillow 9.5.0
pip 22.3.1
protobuf 3.20.1
pyparsing 3.1.2
python-dateutil 2.9.0.post0
pytz 2024.1
PyYAML 6.0.1
scikit-learn 0.24.2
scipy 1.7.3
setuptools 65.6.3
six 1.16.0
tensorboard 1.15.0
tensorflow 1.15.1+git06e2e8aa.dtk2404
tensorflow-estimator 1.15.1
termcolor 2.3.0
threadpoolctl 3.1.0
typing_extensions 4.7.1
Werkzeug 2.2.3
wheel 0.38.4
wrapt 1.16.0
zipp 3.15.0
```
# 测试
## 用CIRI-deep进行预测 ## 用CIRI-deep进行预测
``` ```
python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_totalRNA.tsv -seqFeature ./demo/cisfeature.tsv -splicing_max ./demo/splicingamount_max.tsv -predict_list ./demo/predict_list.txt -model_path ./models/CIRIdeep.h5 -outdir ./outdir -RBP_dir ./demo/RBPexp_total -splicing_dir ./demo/splicingamount python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_totalRNA.tsv -seqFeature ./demo/cisfeature.tsv -splicing_max ./demo/splicingamount_max.tsv -predict_list ./demo/predict_list.txt -model_path ./models/CIRIdeep.h5 -outdir ./outdir -RBP_dir ./demo/RBPexp_total -splicing_dir ./demo/splicingamount
``` ```
输出文件在outputdir下
![Alt text](./images/image3.png)
## 用CIRI-deepA进行预测 ## 用CIRI-deepA进行预测
``` ```
python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_polyA.tsv -seqFeature ./demo/cisfeature.tsv -predict_list ./demo/predict_list.txt -model_path ./models/CIRIdeepA.h5 -outdir ./outdir -RBP_dir ./demo/RBPexp_polyA --CIRIdeepA python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_polyA.tsv -seqFeature ./demo/cisfeature.tsv -predict_list ./demo/predict_list.txt -model_path ./models/CIRIdeepA.h5 -outdir ./outdir -RBP_dir ./demo/RBPexp_polyA --CIRIdeepA
``` ```
输出文件在outputdir下
![Alt text](./images/image4.png)
# 应用场景
# 参考文档
## 算法类别
ai for science
## 行业
科研
## 医疗
科研 高校
# 源码仓库及问题反馈
```
git@developer.sourcefind.cn:modelzoo/cirideep.git
```
# 参考资料
``` ```
https://github.com/gyjames/CIRIdeep.git git clone https://github.com/gyjames/CIRIdeep.git
``` ```
\ No newline at end of file
FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
RUN source /opt/dtk-24.04.1/env.sh
RUN cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
ENV LANG C.UTF-8
...@@ -3,4 +3,6 @@ matplotlib==3.3.4 ...@@ -3,4 +3,6 @@ matplotlib==3.3.4
numpy==1.19.2 numpy==1.19.2
pandas==1.1.5 pandas==1.1.5
scikit-learn==0.24.2 scikit-learn==0.24.2
protobuf==3.20.1
h5py<3.0.0
#python #python
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