課程資訊
課程名稱
 基礎單細胞定序資料分析實作
Basic Single-cell RNAseq Data Analysis 
開課學期
 111-2 
授課對象
 生命科學院  生化科技研究所  
授課教師
 林建達 
課號
 BST5065 
課程識別碼
 B22EU0690 
班次
  
學分
 3.0 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期二7,8,9(14:20~17:20) 
上課地點
 農化第五 
備註
 本課程以英語授課。學士班系定必修科目B群組之一；碩士班A群組必修10學分課程之一。
總人數上限：30人 
  
課程簡介影片
 
核心能力關聯
 本課程尚未建立核心能力關連
課程大綱
為確保您我的權利,請尊重智慧財產權及不得非法影印
課程概述

This course will provide comprehensive overviews and basic data analysis for single-cell RNA-seq. The introduction and hands-on workshops for research methods will be conveyed in this class. Students are supposed to work on their own datasets or public datasets to demonstrate their projects in the final classes.

About the course registration(要加簽的同學注意！) :
This class is type 3 selection method(三類加簽), which means we’re not giving out any class permission number(不會發放授權碼). But teacher wants to raise the upper limit of the number of sutdents for those who came to the class today, and it can’t be fair by doing the type 3 selection method. So teacher has decided to sign your course-add with Petition of Instructor’s Consent(教師同意加簽單/人工加簽) at week 3. Remember to sign the instructor’s consent then! 

課程目標
 The major goal is to establish students’ essential knowledge and basic pipelines of bioinformatics for single-cell RNA-seq. The course will also train students to design and analyze their possible future experiments for scRNA-seq through hands-on workshop in the class. 
課程要求
 Students with no experiences in bioinformatics are welcome for the class. This course is exclusively offered to the undergraduate and graduate students in the Department of Biochemical Science and Technology. The suggest prerequisites for this course are “Programming Skills for Life Science” 「程式設計與生命科學」(CLS2001) and “Basic Computer Programming for Life Science” 「生命科學基礎程式設計」(LS5094). Students are supposed to prepare their own laptop for the practice in class. 
預期每週課後學習時數
  
Office Hours
  
指定閱讀
  
參考書目
  
評量方式
(僅供參考)
    
針對學生困難提供學生調整方式
  
上課形式
作業繳交方式
 個人報告取代團體報告
考試形式
 書面(口頭)報告取代考試
其他
課程進度
週次
日期
單元主題
Week 1
 2023/02/21  Introduction of Next Generation Sequencing (NGS), experimental design, and course outlines 
Week 2
 2023/02/28  Holidays 
Week 3
 2023/03/07  Single-cell RNA sequencing (scRNA-seq) introduction
-Introduction and basic work flow for single-cell RNA sequencing 
Week 4
 2023/03/14  Basic R programming and scRNA-seq data download
-Installation of R and RStudio
-scRNA-seq data download from public dataset 
Week 5
 2023/03/21  scRNA-seq data download
-SRA Toolkit
-scRNA-seq data download from public dataset (NCBI) 
Week 6
 2023/03/28  scRNA-seq data analysis on example dataset
-Setup “Seurat” Object, Data preprocess, Data normalization.  
Week 7
 2023/04/04  Holidays 
Week 8
 2023/04/11  scRNA-seq data analysis on example dataset
- Feature selection, Data scaling, PCA 
Week 9
 2023/04/18  scRNA-seq data analysis on example dataset
- Selection of data dimensionality, Cell clustering, UMAP/tSNE, Identify cluster biomarkers 
Week 10
 2023/04/25  scRNA-seq data integration
-Introduction of scRNA-seq data integration
-Perform integration, identify conserved cell type markers and differential expressed genes across conditions, SCTransform 
Week 11
 2023/05/02  Multimodal data analysis
-Introduction of CITE-seq
-Using Seurat with multimodal data (RNA+ADT)
-WNN on multimodal data (RNA+ADT) 
Week 12
 2023/05/09  Mapping and annotating datasets
-Mapping and annotating query datasets
-Multimodal reference mapping 
Week 13
 2023/05/16  Group 1 Project presentation:
Use their own datasets or public datasets to demonstrate their own project by the techniques learned from the class. Oral presentation (10 mins/person) and a written report are both needed for the final grade.  
Week 14
 2023/05/23  Group 2 Project presentation:
Use their own datasets or public datasets to demonstrate their own project by the techniques learned from the class. Oral presentation (10 mins/person) and a written report are both needed for the final grade.  
Week 15
 2023/05/30  Group 3 Project presentation:
Use their own datasets or public datasets to demonstrate their own project by the techniques learned from the class. Oral presentation (10 mins/person) and a written report are both needed for the final grade.  
Week 16
 2023/06/06  Group 4 Project presentation:
Use their own datasets or public datasets to demonstrate their own project by the techniques learned from the class. Oral presentation (10 mins/person) and a written report are both needed for the final grade.  
Week 17
 2023/06/13  Group 5 Project presentation:
Use their own datasets or public datasets to demonstrate their own project by the techniques learned from the class. Oral presentation (10 mins/person) and a written report are both needed for the final grade.