Intro to Bioinformatics

Our Focus

What makes this course unique?

About the Course

What you can expct to learn

We teach everything necessary to do your sequencing analysis

We start our course by talking about various sequencing platforms and go into detail about experiment design and sequencing technology selection.

In the CS module we introduce students to Linux and the Shell. Students learn about servers and job submission. We talk about sequencing data access and quality control. Students learn programming in R and basic scripting in Linux

Statistics module covers Significance testing (p-value), normalization methods and data distributions. We will discuss in detail about various normalization methods and their applicability for different types of data.

Bioinformatics module is the essence of this course. Having learnt basic computer science and statistics skills we will learn about open source tools (including R packages available in "BioConductor") that help us with specific analyses like ChIP/RNA-seq, Variant/SNP calling and Graphics.

Sequencing Techniques
Platforms, Merits of one vs. another, Sequencing background
Computer Science
Linux, Programming in R, Functions, Variables, Data Structures, File Systems, Scripting, Parallel Job Submission, FTP etc.
statistics
P-Value, Normalization techniques, Data distributions in the NGS context, Statistical Power
Bioinformatics
Read Alignment algorithms, Bioconductor packages in R, ChIP/RNA-Seq, Variant / SNP Calling, Genome Browsers, Graphics / Heatmaps, GSEA & Pathway Analysis

OUR TEAM

We've put together the best team to deliver the best instruction

Vishal Thapar, Ph.D.

Staff Scientist, Mass General Hospital Cancer Center, Department of Pathology, MGH

Dr. Thapar has a Ph.D. in Computer Science and a post doc in Computational Biology from Cold Spring Harbor Lab. He has worked on Cancer Genetics in Dr. Scott Lowe’s Lab at MSKCC and currently works with the Cancer Center and Department of pathology at MGH

Dr. David T. Ting

Assistant Physician Mass General Cancer Center Assistant Professor in Medicine Harvard Medical School

Ting Laboratory has been utilizing innovative microﬂuidic chip technologies to capture circulating tumor cells (CTCs) in the blood of pancreatic cancer patients as a means to understand why pancreatic cancers spread so quickly and as a potential non-invasive tool to diagnose our patients earlier.

Martin Aryee, Ph.D.

Assistant Professor, Department of Pathology, Massachusetts General Hospital & Harvard Medical School, Assistant Professor in the Department of Biostatistics, Harvard TH Chan School of Public Health, Associate Member, Broad Institute of Harvard and MIT

Martin received his PhD in Biostatistics from the Harvard School of Public Health in 2008, and completed a post-doctoral fellowship at the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center.

Ben Wittner, Ph.D.

Staff Scientist, Mass General Hospital, Cancer Center

Dr. Wittner is a Staff Scientist in the Massachusetts General Hospital Center for Cancer Research and an Instructor in Medicine at the Harvard Medical School. His package on Clustering and Heatmaps has been used in many top tier journal publications

Feedback from students

Strengths: “Hands-on training. Accessible to complete beginners like myself” “Your availability step-by-step coaching” “The depth of knowledge of the instructor. I felt that the instructor was very approachable. I enjoyed the smaller class size that allowed students to engage with each other and with the instructor.”

Spring 2016 Course Participant(s)

PHD, MD, Post Doctoral Student

1. Instructor was pleasant and extremely helpful 2. The practical parts of the course were the most beneficial and helpful in learning 3. provided a general outline and a broad overview of the bioinformatics pipelines 4. provided a good overview of teh sequencing technologies and limitations in data analysis 5. provided the working tools necessary to understand, analyze and extrapolate conclusions from NGS data

Spring 2016 Course Participant

PHD, MD, Post Doctoral Student

Having several available pipelines for analyzing a host of sequencing data is very cool. I think the single biggest strength of the course was overcoming my fear of big data/sequencing pipelines, and showing me that you don’t need a Ph.D. in bioinformatics to do employ basic sequencing strategies

Spring 2016 course participant

Assistant Professor, MGH Cancer Center

This is the best bioinformatics introduction course that I have ever taken. Vishal is a fantastic instructor. He is extremely patient with each student and willing to spend a lot of his personal time on answering their questions (including nights and weekends). His classes are fun and interactive. Vishal has a good knowledge of his teaching material. His course covers a variety of topics from the very basic Unix skill to the latest sequencing analysis tools in the bioinformatics field. He selected the most useful/reliable analysis tools, and designed individual lectures to explain their concepts and functions. Then, he arranged practical sections in the same week to ensure that students learned how to use those analysis tools. Instead of asking students to simply copy or memorize his template codes, Vishal encouraged them to develop their own skills to write scripts and trouble-shoot bugs. That is very inspiring! I truly enjoy the learning experience in Vishal’s classes.

Spring 2016 Course Participant

PHD, Post Doctoral Student

“Very relevant, r series was great. YouTube videos are great.” “Vishal was wonderful! Patient, kind and very knowledgable. I have a much better understanding of NGS data and analysis. I really appreciated the videos online to be able to be able to re-watch some lecture material.”, “Clear outline of material and how to get from sequencing to DE analysis. Vishal’s careful attention to detail.”

Spring 2016 Course Participant(s)

MD/PHD