DAY 1: Advanced Microarray Data Analysis

           2월 24일(월)

시간

  주  제

강 사

8:30 ~ 9:30

9:30 ~ 9:50

김주한 교수

9:50 ~ 10:40

Gene Expression Analysis
- Normalization
- Differential Expression Analysis
- Classification Analysis

김주한 교수
(서울의대)

10:50 ~ 12:10

실 습 I: Bioconductor
          t-test, SAM, ANOVA, FDR
          LDA, DTs, SVM

이수연, 박지혜

12:10 ~ 13:10

  중  식

13:10 ~ 14:00

Clustering and eQTL Analysis of Gene Expression Data
- Clustering Analysis
- Cis- and trans-expression eQTL
- eQTL hotspots
- Connection to GWAS

손경아 교수
(아주대)

14:10 ~ 15:30

실 습 II: KNN, SOM, HC, PCA
           Identify eQTL hotspot
           eQTL resource

임재현, 안선주

15:40 ~ 16:30

Gene-set Approaches & Prognostic Subgroup Prediction
- Gene Ontology & Pathway Analysis
- Gene Set Enrichment Analysis
- Prognostic Subgroup Prediction

조성범 박사
(국립보건연구원)

16:40 ~ 18:00

실 습 III: Gene Set Enrichment Analysis
           Cox-PH, Log Rank Test
           David, ArrayXPath

김기태, 백수연

DAY 2: Next Generation Sequencing & Personal Genome Data Analysis

          2월 25일(화)

시간

  주  제

강 사

8:30 ~ 9:30

9:30 ~ 9:50

Next Generation Sequencing & Personal Genome Data Analysis

 김주한 교수

9:50 ~ 10:40

NGS Platforms and Applications
- Current NGS Platforms
- NGS Data Formats
- NGS Data Analysis Technologies
- NGS Applications

김지훈 박사
(랩지노믹스)

10:50 ~ 12:10

실 습 I: NGS Data Processing
         NGS Data Format Converting
         NGS Visualization Tools

서희원, 임재현

12:10 ~ 13:10

  중  식

13:10 ~ 14:00

NGS Data Analysis
- Sequence Alignment Algorithms
- Whole Genome and Exome Data Analysis
- Variation Detection and Reference Genome

최무림 교수
(서울의대)

14:10 ~ 15:30

실 습 II: Exome Sequencing Alignment
          SNP and Indel Identification
          Variation Filtering

박찬희, 서희원

15:40 ~ 16:30

Personal Genome Interpretation
- Phenotype Annotation
- Genetic Risk Prediction
- Healthcare Application

김주한 교수
(서울의대)

16:40 ~ 18:00

실 습 III: SNP Prioritization
            Genetic Risk Prediction methods
            Resources for Personal Genome Interpretation
            (dbGAP, PheGeni, SNPedia, PhenoDB)

이수연, 박지혜

DAY 3: RNA-seq Data Analysis

          2월 26일(수)

시간

  주  제

강 사

8:30 ~ 9:30

9:30 ~ 9:50

RNA-seq Data Analysis

 김주한 교수

9:50 ~ 10:40

RNA-Seq Expression Profile Analysis
- Read Alignment Methods
- Expression Quantification Strategy
- Differentially Expressed Genes Identification
- Expression Profile Analysis

정제균 박사
(삼성유전체연구소)

10:50 ~ 12:10

실 습 I: Read alignment with TopHat,
          Expression Quantification with Cufflinks
          RNA-Seq Gene Expression Analysis

임재현, 서희원

12:10 ~ 13:10

  중  식

13:10 ~ 14:00

Sequence-level Transcriptome Analysis
- Novel Transcript Discovery
- Alternative Splicing Identification
- RNA-editing Analysis
- New/Fusion Gene Identification

김주한 교수
(서울의대)

14:10 ~ 15:30

실 습 II: Alternative Splicing Identification
           RNA-DNA Difference (RDD) Analysis
           RNA Editing Site Annotation

이수연, 백수연

15:40 ~ 16:30

Non-coding RNAs in RNA-Seq Data
- miRNA Expression Profiling
- miRNA Target Gene Prediction
- Non-coding RNA Characterization

남진우 교수
(한양대)

16:40 ~ 18:00

실 습 III: miRNA Sequencing Data Process
           miRNA Expression Profiling
           non-coding RNA Resources

서희원, 임영균

DAY 4: Exome Sequencing and Cancer Genome Bioinformatics

          2월 27일(목)

시간

  주  제

강 사

8:30 ~ 9:30

9:30 ~ 9:50

Exome Sequencing and Cancer Genome Bioinformatics

 김주한 교수

9:50 ~ 10:40

Exome Sequencing and Rare Disease
- Exome Sequencing Data
- Exome Sequencing of Rare Disease
- Variant Analysis and Annotation

김남신 박사
(생명공학연구원KOBIC)

10:50 ~ 12:10

실 습 I: Trio-Exome-Sequencing Data Analysis
          Known Variant Filtering
          Detection of Disease-causing Variations
          Disease Gene Prioritization

서희원, 김기태

12:10 ~ 13:10

  중  식

13:10 ~ 14:00

Cancer Genome Bioinformatics
- Cancer Genome Analysis
- Identifying Genomic Rearrangement
- Gene Fusion Analysis
- Survival Analysis

송영수 교수
(한양의대)

14:10 ~ 15:30

실 습 II: Fusion Gene Analysis from RNA-seq
          Network and Survival Analysis
          Resources for Cancer Research:
          cBioPortal, COSMIC, CCLE, OncoMap

이수연, 백수연

15:40 ~ 16:30

Copy Number and Genomic Rearrangement
- CNA Identification in Cancer Genome
- Copy Number Data Processing
- Genomic Rearrangement

김봉조 박사
(국립보건연구원)

16:40 ~ 18:00

실 습 III: Cancer Genomic Rearrangement            Identification of CNV Regions
           CNV Database

임재현, 임영균

DAY 5: Translational Bioinformatics: Thousands of Public Data Analysis

          2월 28일(금)

시간

  주  제

강 사

8:30 ~ 9:30

9:30 ~ 9:50

Translational Bioinformatics: Thousands of Public Data Analysis

 김주한 교수

9:50 ~ 10:40

The Cancer Genome Atlas (TCGA) Project and Cancer Genome Research
- TCGA Introduction
- TCGA Data and Scientific Findings
- Impact of TCGA and Future

김태민 교수
(카톨릭의대)

10:50 ~ 12:10

실 습 I: TCGA Somatic Mutation Landscape
          Find Significantly Mutated Genes
          Identify Driver Groups of Mutations

김기태, 임재현

12:10 ~ 13:10

  중  식

13:10 ~ 14:00

The Encyclopedia of DNA Elements (ENCODE) and Human Genome Research
- ENCODE Overview
- New Insights into the Human Genome
- Gencode project and UCSC Genome Browser

홍경원 박사
(질병관리본부)

14:10 ~ 15:30

실 습 II: Explore ENCODE Data at UCSC Genome Browser
          Identify Transcription Factor Binding Loci from ChIP-seq Data
          Detection of Regulatory SNPs

임재현, 임영균

15:40 ~ 16:30

Genome-Phenome-EMR Integrative Analysis
- EMR and beyond GWAS
- Phenome-Wide Association Study (PheWAS)
- Environment-Wide Association Study (EWAS)

김주한 교수
(서울의대)

16:40 ~ 18:00

실 습 III: Phenotype Extraction from eMERGE Network Data
           Integrating Genetics: EMR-based Phe-WAS
           PheWAS View for Visualization 

이계화, 서희원