No prior coding experience necessary
We assume no prior coding / computer science knowledge in this course. We go over everything “computer science-y” in a user friendly terminology
Realistic Lesson plans
If everyone could finish a course in one week then we would not need this course. We give you enough time to practice what you learn so that you retain what you learn
Content is customized based on the needs of our students. If students would rather study ChIP-Seq as opposed to Variant Calling, we do that.
Keeping our class size under 15 students helps us give personalized attention to all students. You also get free tutoring after
About the Course
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.
Platforms, Merits of one vs. another, Sequencing background
Linux, Programming in R, Functions, Variables, Data Structures, File Systems, Scripting, Parallel Job Submission, FTP etc.
P-Value, Normalization techniques, Data distributions in the NGS context, Statistical Power
Read Alignment algorithms, Bioconductor packages in R, ChIP/RNA-Seq, Variant / SNP Calling, Genome Browsers, Graphics / Heatmaps, GSEA & Pathway Analysis
Vishal Thapar, Ph.D.
Dr. David T. Ting
Martin Aryee, Ph.D.
Ben Wittner, Ph.D.
Feedback from students
This course will cover detailed analysis for Single Cell RNA-seq data Details What is scRNA-seq and Why do we need it? (Lecture 1) Protocols and methodology for scRNA-seq setup (Lecture 1) Challenges, Experimental Methods, Platforms & Computational Analysis (Lecture 2-6) This course will deal with the computational analysis of the data obtained from scRNA-seq experiments. Read more about Single Cell Analysis Course[…]
Hourly timeline DISCLAIMER: This can not be applied and should not be applied to patient data 9 – 9:15 am Introduction to the course 5 Minute Goals for this course and Expectations 5 minutes Next 2 days, what will we cover course content 5 minutes, Software we will be using for this course Read more about Course Curriculum (Online Bioinformatics)[…]
Thank you for your interest in Bioinformatics. Please fill out the form at this link: Online Bioinformatics Application to register for the 1 day Online Bioinformatics course and send it to me via email at email@example.com to reserve a spot for the next session to be held on March 7th 2019. Please fill out the form Read more about Application form and Information[…]
________________________________________ CURRICULUM FOR 2018 ______________________________________ What will the students learn? Server and Cluster usage in Linux Basic Programming in R Basic Statistics Introduction to Next Gen Sequencing technologies NGS Data Quality Control and Alignment Downstream analysis of NGS Data including RNA-seq, ChIP-seq, Gene Set Enrichment Analysis, SNP calling, Pathway analysis, publication quality Heatmaps and graphics Read more about Course Curriculum 2018 (Semester Course)[…]
“` DataCamp offers online tutorials and courses to help students learn R and Python for data science. You can try their free courses here: Learn R with Introduction to R Learn Python with Intro to Python for Data Science Another Intro course in Python can be found here: https://www.guru99.com/python-tutorials.html
Thank you so much for your interest in this Course. Here is a presentation for the intro session to be held on August 17th and August 31st, 2016 Demo_Presentation_Bioinformatics If you are interested and want to attend the course, please fill out this form and get back to me before September 2nd 2016 for the Read more about Information Session and Application (Fall 2016)[…]
Thank you so much to all who showed up for the course. It was really nice to present the details. I am attaching the slides for those who could not make it to the class. Demo_Presentation_Bioinformatics If you are interested and want to attend the course, please fill out this form and get back to Read more about Information Session Updates (Spring 2016)[…]
In case you missed it, here are the highlights from last time followed by Course Details for this semester! What will the students learn? Server and Cluster usage in Linux Basic Programming in R Basic Statistics Introduction to Next Gen Sequencing technologies NGS Data Quality Control and Alignment Downstream analysis of NGS Data including RNA-seq, Read more about Course Details[…]
Welcome to Intro to Bioinformatics. Please find the highlights of our course from last semester here. We’ll be holding an information session for the new course which may begin in the second week of March, 2016, on Feb 24th (tentatively). Please sign up via our website to attend the info session.