AI 및 Data Analysis/Code21 [ProtoCell 4P] scRNA Analysis 1. Setupgit clone https://github.com/Teddy-XiongGZ/ProtoCell4P.git# 가상환경 생성, 패키지 설치python -m venv venvsource venv/bin/activatepip install -r requirements.txt# 참고로, 설치해야할 패키지가 하나 더 있다. requirements.txt에 추가해주자.# tensorboard# 다음 명령으로 pip 가 dependency resolution 과정에서 뭘 설치하려는지 로그 볼 수 있습니다:# 여기서 어떤 패키지가 build 하려다가 에러가 나는지 정확히 알 수 있어요.# pip install -r requirements.txt -vvv https://github.com/Teddy-Xion.. 2025. 4. 10. [Hierarchical MIL] Preprocessing Create '.h5ad' .h5ad 란?구성요소내용adata.X유전자 발현 행렬 (filtered X, shape = cells × genes)adata.obs셀 메타데이터 (meta)adata.var유전자 메타데이터 (adata.var.index = genes)📦 AnnData 객체 형태AnnData object with n_obs × n_vars = [셀 수] × [유전자 수] obs: patient, label, cell_type_annotation, ... var: gene names 즉, 각 셀(row)마다:유전자 발현 값 (X)label, patient ID, cell type 주석 등 (obs)gene names (var)이게 통합된 형태로 저장됩니다.[Hierarchical MIL] Preprocessing .. 2025. 3. 28. [Hierarchical MIL] Code ; Train.py 논문Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Datahttps://www.biorxiv.org/content/10.1101/2025.02.10.637389v1.full.pdf 논문 정리2025.03.22 - [AI 및 Data Analysis/Paper] - [Hierarchical MIL] Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Data [Hierarchical.. 2025. 3. 27. [Hierarchical MIL] scRNA Analysis 논문Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Datahttps://www.biorxiv.org/content/10.1101/2025.02.10.637389v1.full.pdf 논문 정리2025.03.22 - [AI 및 Data Analysis/Paper] - [Hierarchical MIL] Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Data [Hierarchical .. 2025. 3. 24. [Hierarchical MIL] Exploratory Data (Summary) 논문Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Datahttps://www.biorxiv.org/content/10.1101/2025.02.10.637389v1.full.pdf 논문 정리2025.03.22 - [AI 및 Data Analysis/Paper] - [Hierarchical MIL] Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq Data [Hierarchica.. 2025. 3. 22. [ScRAT] Exploratory Data (Summary) ScRAT를 활용하여, scRNA 데이터를 분석해 보았다. 2025.03.20 - [AI 및 Data Analysis/Code] - [ScRAT] scRNA Analysis [ScRAT] scRNA AnalysisPaper : Phenotype prediction from single-cell RNA-seq data using attention-based neural networks https://academic.oup.com/bioinformatics/article/40/2/btae067/7613064 본 논문에서 언급된 ScRAT 방법으로 scRNA 분석하기 https://github.com/yuzhendoraemin.tistory.com데이터에 대해 살펴보자.COMBAT와 Haniffa 데이터는 →.. 2025. 3. 22. 이전 1 2 3 4 다음
