Bioinformatics Intensive Practical Course ‘KYOTEN’ FY 2020のご案内


This year’s KYOTEN’s Bioinformatics(BI) Intensive Practical Course will consist of 8 lectures (including one special lecture). The course will be taught in English (英語) and will be held online using Zoom. After completing the course, participants should have a basic practical working-knowledge of the Next Generation Sequencing (NGS) Data Analysis, be able to use the command line utility (‘terminal/shell’), independently execute, modify and write simple and reproducible NGS pipelines as well as R codes to perform differential gene expression, pathway functional analysis and single cell RNA-seq data analysis.

Participants will be responsible for the setup of their own computational environment (instructions how to instal the software will be provided) on one of the following operating systems: macOS 10.13+, *Linux, **Windows 10/8/7.

Before starting the course, all participants will also need to have the following software installed:
(1) R statistical software 4.0+
(2) RStudio Desktop 1.3+
(3) ***Command Line Utility (terminal/shell) and vim/vi text editor
(4) HISAT2 2.2+ (sequence alignment program)
(5) bedtools 2.29+
(6) IGV 2.8+ (Integrative Genomic Viewer).

To make the online course more efficient, working and documented scripts will be provided one week before each lecture together with the next lecture presentation. Participants will be required to check whether they can execute the scripts on their own computer and are encouraged to look at the lecture slides in advance to get familiar with English terminology. After the 2nd lecture, participants will also be given a basic R homework assignment to get more familiar with the basics of R (reading/writing files, inspecting the data, basic plotting commands, etc.).

For all course announcements and software requirements, please follow the Course Dropbox Account. Help will be provided through the Course Slack Channel.

*Linux – latest version of Ubuntu/Debian, Fedora/RedHat, SLES/OpenUSE should be compatible with the required BI software
**Windows 10 is preferred
***Command Line Utility (‘terminal/shell’) and vi/vim text editor can be potentially used from RStudio

General Course Info
Course Fee

English (英語)

Online: Zoom

Course Audience
Kyoten Collaborators (no prior knowledge of bioinformatics is required)

Number of Participants
20 participants (maximum)
(priority will be given to this year’s Kyoten collaborators, but other applications might be accepted untill the limit of 20 participants is reached)

Jordan Ramilowski, PhD(YCU/RIKEN

Akira Nishiyama, PhD
Koichi Murakami, MD

Course Resources
Online Resources and Support
Course Dropbox Account (provided later)
Course Slack Channel (provided later)

Availability of Lecture Material
R code(s) and/or other scripts used for the lectures will be available in advance.
Course materials (PowerPoint or PDF slides) will be available in advance.

PC Environment
macOS 10.13+, *Linux, **Windows 10/8/7

*Linux – latest version of Ubuntu/Debian, Fedora/RedHat, SLES/OpenUSE should all be compatible with the required software. 
**Windows 10 is preferred.

Please let us know (using Course Slack channel) if you have any questions related to your PC Environment.

Preparation Required in Advance
Working Mac, Linux, Windows computer (please refer to Requirements: “PC Environment”) with the internet connection and the following software installed:
   (1) R statistical software 4.0+
   (2) RStudio Desktop 1.3+ (development environment for R)
   (3) *Command Line Utility (‘terminal/shell’) & vim/vi  (text editor)
   (4) HISAT2 2.2+ (sequence alignment program)
  (5) bedtools 2.29+
   (6) IGV 2.8+ (Integrative Genomic Viewer)

*Command line utility (‘terminal/shell’) and vi/vim text editor can be also used  from RStudio.

Please let us know (using Course Slack channel) if you have any questions on installing the required software.

Lectures (8 total)
7 Lectures + 1 Special Lecture
2 hours/class:
~ 1h:45min lecture + ~15min discussion
December 18 to February 22 (FY2020)

Lecture 12020  December 18(Fri)17:30~19:30
Lecture 22021 January 4(Mon)17:30~19:30
Lecture 32021  January 18(Mon)17:30~19:30
Lecture 42021 January 26(Tue)17:30~19:30
Lecture 52021 February 1(Mon)17:30~19:30
Lecture 62021 February 8(Mon)17:30~19:30
Lecture 72021 February 15(Mon)17:30~19:30
Lecture 82021 February 22(Mon)17:30~19:30

Lecture 1: Course Overview & Introduction to Bioinformatics
Course Introduction
Introduction to Bioinformatics (BI) & Next Generation Sequencing (NGS)
Check of the Installed (required) Software

Lecture 2: Next Generation Sequencing Pipelines
Public NGS Data Sets (RNA-seq, ATAC-seq, Chip-seq, etc.)
Overview of NGS Pipelines
Command Line Tool (‘terminal/shell’) & vim/vi text editor

Lecture 3: Sequence Quality Control, Alignment and Visualization
NGS Data Quality Control (QC)
Sequence Alignment to the Reference Genome (HISAT2)
IGV (Integrative Genomic Viewer)

Lecture 4: Preparation and Exploration of Gene Expression Data
Gene Models for Reference Organisms (human and mouse)
Making Expression Tables (bedtools)
Expression Data Normalization & Exploration (PCA plots)

Lecture 5: Functional Studies (1): Differential Gene Expression Analysis
Differential Gene Expression using EdgeR

Lecture 6: Functional Studies (2): Gene Set Enrichment Analysis
Pathway Enrichment and Over-representation (online tools; R)
Understanding the Gene Set Background & Interpreting the Results

Lecture 7: Single-cell RNA-seq Data Analysis
scRNA-seq Data Analysis using Seurat

Lecture 8: Special Lecture: Reproducible and Scalable BI
Version Control (GitHub/GitLab) 
Introduction to High-Performance (HP) & Cloud Computing
Course Summary