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Online Course

Introduction to Proteogenomics

Indian Institute of Technology Bombay and NPTEL via Swayam

6
Found in Biology, Engineering

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Overview

Cancer research has been significantly aided by advancements in proteogenomics technologies, where proteomics information derived from mass spectrometry is used to complement genomics using next generation sequencing. With the recent advent of Cancer Moonshot Project, the critical role that proteogenomics can play in improving cancer patient treatment is increasingly being recognized. This course will utilize advanced genomic and proteomic technologies and their data from high-quality human biospecimens to identify potentially actionable therapeutic molecular targets. This course is a part of a workshop by experts in the fields of proteomics and proteogenomics in cancer research from the Broad Institute of MIT and Harvard and Indian Institute of Technology Bombay. The course will comprise interactive lectures with case studies, hands-on sessions and demonstrations on proteogenomics aimed at accelerated understanding of cancer and will cover the principles of proteogenomics followed by experimental sessions, where proteomics data using LC-MS/MS will be processed and analyzed. The next step will be to integrate the proteomics data with genomics data, from The Cancer Genome Atlas for the proteogenomics analysis. Lectures and demonstrations on different computational methods will be performed for statistical data analysis of proteogenomics data.

INTENDED AUDIENCE: Biotechnology or Engineering background students having interest in latest technologies,(BE/B.Tech)
Biotechnology. Students with science or engineering background but course is open to all
PREREQUISITES: Nill
INDUSTRY SUPPORT: Thermofisher Scientific, Illumina

Syllabus

COURSE LAYOUT

Week 1: Proteogenomics overview- Part I, Proteogenomics overview- Part II, Introduction to Genomics- Part I : Gene
sequencing and mutations Introduction to Genomics-Part II : Sequence alignment, Introduction to Genomics-
Part III :Transcriptome, SL1: Advancement in Cancer Genomics, SL2: Advancement in Cancer Genomics
Week 2: Introduction to Genomics IV : Epigenome, Introduction to Genomics : cBioPortal, Genotype, Gene expression &
Phenotype - Part I, Genotype, Gene expression & Phenotype- Part II, An overview of NGS technology, SH1:
NGS-Sequencing by synthesis, SH2: NGS- Sequencing by synthesis
Week 3: Introduction to Proteomics, Proteomics: Sample Prep & Protein Quantification, Proteomics: Sample Prep &
Protein Quantification (Hands-on), Introduction to MS-based Proteomics- Part I, Introduction to MS-based
Proteomics- Part II, SL 3: Applications of NGS – Ion Torrent, SL4: Applications of NGS – Ion Torrent
Week 4: Introduction to MS-based Proteomics- Part I (Hands-on), Introduction to MS-based Proteomics- Part II
(Hands-on), Data analysis: Normalization, Data analysis: Batch Correction and Missing values, Data analysis:
Statistical Tests, SH3: NGS- Ion Torrent, SH4: NGS- Ion Torrent
Week 5: Machine learning and Clustering, Hypothesis testing, ProTIGY- Part I,ProTIGY- Part II, Proteogenomics
approach to unravel proteoforms, SL5: Genomic Analysis using Droplet PCR, SL6: Genomic Analysis using
Droplet PCR
Week 6: Workflow to Automated Data Processing, Introduction to Fire Cloud, Fire Cloud and Data Model, Bioinformatics
solutions for ‘Big Data’ Analysis- Part I, Bioinformatics solutions for ‘Big Data’ Analysis-Part II, SH5: Genomic
Analysis using Droplet PCR, SH6: Genomic Analysis using Droplet PCR
Week 7: Data Science infrastructure management- Part I, Data Science infrastructure management- Part II, Data
Science infrastructure management- Part III, DIA-SWATH Atlas-Part I, DIA-SWATH Atlas-Part II, SL7:
Introduction to Targeted Proteomics, SH7: Data Analysis using Skyline
Week 8: Human Protein Atlas-Part I Clinical, Human Protein Atlas-Part II, Affinity based proteomics & HPA, Clinical
Considerations for OMICS-Part I, Considerations for OMICS- Part II, SL8: Proteomics: PTMs, SL9: Clinical
Proteomics
Week 9: ntroduction to Proteogenomics-Part I, Introduction to Proteogenomics-Part II, Sequence centric
proteogenomics, Gene Variant Analysis, Proteomics in Clinical studies,SH8: ProTIGY
Week 10:Supervised Machine learning- Predictive Analysis Part I, Supervised Machine learning- Predictive Analysis
Part II, Supervised Machine learning- Marker Selection, Gene Set Analysis using WebGestalt- Part I, Gene Set
Analysis using WebGestalt- Part II, SH9: Supervised Machine Learning
Week 11:Biological Network Analysis- Part I, Biological Network Analysis- Part II, Mutation and Signaling - Part I,
Mutation and Signaling- Part II, Pathway Enrichment,SH10: Pathway Enrichment and Network Analysis
Week 12:Gene Set Enrichment Analysis (GSEA), Pathway enrichment: GSEA, Linked Omics, Linked Omics
(Hands-on), Proteogenomics Conclusions, SL10: Topics in Proteogenomics- Malaria and Cancer case study


Taught by

Prof. Sanjeeva Srivastava

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