Course Identification

Title:

Bioinformatics analysis of Next Generation Sequence (NGS) data

Code:

20193091

Lecturers and Teaching Assistants

Lecturers:

Dr. Ester Feldmesser, Dr. Dena Leshkowitz, Dr. Tsviya Olender, Dr. Hadas Keren-Shaul, Dr. Ron Rotkopf, Dr. Bareket Dassa, Dr. Noa Wigoda

TA's:

N/A

Course Schedule and Location

Year:

2019

Semester:

First Semester

When / Where:

Thursday, 09:15 - 12:00, WSoS, Rm B

First Lecture:

08/11/2018

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; 3.00 points
Life Sciences (Molecular and Cellular Neuroscience Track): Lecture; Elective; 3.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; Elective; 3.00 points
Life Sciences (Computational and Systems Biology Track): Lecture; Elective; 3.00 points

Comments

For second year MSc and forward. Not for first year MSc students.

Prerequisites

No

Restrictions

Participants:

32

Language of Instruction

English

Registration by

Registration By:30/10/2018

Attendance and participation

Required in at least 80% of the lectures

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

Attendance

20%

Assignments:

40%

Final:

40%

Evaluation Type

Examination

Scheduled date 1

Date / due date

07/03/2019

Location

WSoS, Rm C

Time

1000-1200

Remarks

N/A

Scheduled date 2

Date / due date

19/03/2019

Location

WSoS, Rm B

Time

1000-1200

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

2

Syllabus

Introduction to Illumina NGS technology
NGS applications and introduction to analysis
Illumina Primary Analysis Pipeline & Quality Control
Sequence alignment to genome
RNA-Seq gene level differential expression and Mars-seq analysis
RNA-Seq transcript level analysis and de novo transcriptome assembly
Clustering analysis on gene expression data
Functional analysis: Gene Ontology and pathways
Single cell RNA-Seq
Variant detection
Additional genomic technologies: PacBio and 10xGenomics
In-house developed NGS pipelines interface

Learning Outcomes

Upon successful completion of the course students will be able to:

Demonstrate familiarity with the common applications of deep-sequencing.
Discuss the basics steps of data analysis.
Extract the biological meaning of the results.

Reading List

Brown, S. M. Next-generation DNA sequencing informatics: . 2nd ed. Cold Spring Harbor Laboratory Press.
Next-generation genomics: an integrative approach R. David Hawkins, Gary C. Hon & Bing Ren Nature Reviews Genetics 11, 476-486 (July 2010) | doi:10.1038/nrg2795
http://www.nature.com/subjects/next-generation-sequencing

Website

N/A