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CSE-895 Microarray and RNA Sequencing
Campus
RCMS
Programs
PG
Session
Fall Semester 2016
Course Title
Microarray and RNA Sequencing
Course Code
CSE-895
Credit Hours
3-0
Pre-Requisutes
None
Course Objectives
D e s c r i p t i o n
:
Particular emphasis in ‘Microarray and RNA Sequencing’ is placed on the understanding, designing and analysis of microarray and sequencing experiments. This course sheds light on the high throughput trancommentomic technologies that have been applied to look for a holistic view of the underlying biological mechanisms that occur in response to some stimuli. With the passage of time, scientists have designed a number of tools and algorithms to meet the challenge of analyzing the data generated from these techniques. These technologies have been widely adopted in laboratories around the world. The powerful and flexible nature of these techniques has open gates to many areas of research becoming an indispensable tool for biological research. A deep understanding of the designing of these techniques and analysis of the data generated from them has become a necessity in the field of biology and medicine.
Objectives:
Primary focus of the program under which the proposed course will be conducted is
Basic understandings on how to analyze and interpret different trancommentomic data using high through put technologies using R statistical language:
Understand the analysis of microarray data.
Understand the analysis of second generation sequencing data at introductory level.
Read/understand the current literature involving high dimensional Biology. Be able to conduct expression microarray data analyses.
Biological interpretation of data.
Detail Content
Introduction
Overview of Central Dogma of Molecular Biology
High density oligonucleotides
Spotted complementary cDNA technologies
High throughput genomic technologies
Introduction to microarrays, data analysis and R programming
Microarray platforms
Affymetrix structure and function
File formats
Experimental designs
Data Analysis using Bio-conductor, R and Linux
Data pre-processing
Background Correction
Normalization, log transformation
Data manipulation and quality control
Principal component analysis
NUSE and RLE plots
Differential Expression
Overview of statistical techniques and practical application using R and microarray data
Parametric (Pearson, t-test, one way ANOVA)
Non-parametric (Spearman, Wilcoxon)
Multiple Comparison/FDR
Example analysis
RNA Sequencing
Introduction to RNA-seq
RNA seq study design
RNA seq data analysis
Quality Control
Alignment
SNP calling
Fusion alignments
Alternative Splicing
Assembly
Differential Expression
Novel Trancommentome
Example analysis
RNA seq future
Biological Interpretation
Bioinformatics functional tools, gene annotation, databases
Text/Ref Books
DNA Microarray Analysis Using Biocondutor, JarnoTuimala CSC, the Finnish IT center for Science
Statistics and Data Analysis for Microarrays Using R and BioconductorSecond Edition SorinDraghici
Time Schedule
Faculty/Resource Person
Assistant Professor - Dr Mehak Rafiq