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# cirideep
## 论文
# 论文
CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning
https://onlinelibrary.wiley.com/doi/10.1002/advs.202308115 https://onlinelibrary.wiley.com/doi/10.1002/advs.202308115
# 模型结构 ## 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， 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) ![img](./images/image.png)
# 算法原理 ## 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。 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) ![Alt text](./images/image-1.png)
# 环境配置 ## 环境配置
## Docker（方法一） ### Docker（方法一）
``` ```
docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:cirideep docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:cirideep
...@@ -29,16 +29,8 @@ docker run -dit --shm-size 80g --network=host --name=CIRI --privileged --device= ...@@ -29,16 +29,8 @@ docker run -dit --shm-size 80g --network=host --name=CIRI --privileged --device=
docker exec -it CIRI /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） ### Dockerfile（方法二）
``` ```
docker build -t cirideep:latest . docker build -t cirideep:latest .
...@@ -46,7 +38,7 @@ docker run -dit --shm-size 80g --network=host --name=CIRI --privileged --device= ...@@ -46,7 +38,7 @@ docker run -dit --shm-size 80g --network=host --name=CIRI --privileged --device=
docker exec -it CIRI /bin/bash docker exec -it CIRI /bin/bash
``` ```
## anaconda (方法三) ### anaconda (方法三)
1.创建conda虚拟环境： 1.创建conda虚拟环境：
...@@ -63,10 +55,10 @@ pip install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ --trus ...@@ -63,10 +55,10 @@ pip install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ --trus
``` ```
# 预测 ## 推理
## 用CIRI-deep进行预测 ### 使用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
``` ```
...@@ -77,7 +69,7 @@ python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_totalRNA.tsv -seqFeatur ...@@ -77,7 +69,7 @@ python CIRIdeep.py predict -geneExp_absmax ./demo/RBPmax_totalRNA.tsv -seqFeatur
## 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
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