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Your Instructors
We are members (or alumni) of the functional genomics lab of Vishwanath Iyer, UT Austin.
Anna Battenhouse, Associate Research Scientist,
Iyer Lab,- Dr. Daechan Park, Post-doctoral fellow, Georgiou Lab, daechan.park@utexas.edu
- Nathan Abell, Research Assistant, Iyer Lab, abell.nathan@gmail.com
- Amelia Weber Hall, Graduate Student, Iyer Lab, ameliahall@utexas.edu
Goals
- Hands-on, tutorial style – learn by doing
- Cover the NGS tool basics – the first few things you'll do after receiving raw sequences
- Get you comfortable with Linux and TACC – your best "frenemies"
- Make you self sufficient in 4 days to become experts over time
- Show some "best practices" for working with NGS data
Communication
Post its
Green post-it – I'm good at the moment.
Pink post-it – I need a bit of help.
Etherpad
Link to Etherpad: https://etherpad.mozilla.org/yUFlDtWv2c
Use this to post any questions you have about the lessons and tutorials.
Conventions
Text that you find in courier font refers to a program or file name on a computer.
BA English literature, 1978
Commercial software development 1982 – 2007
Joined Iyer Lab 2007 (“retirement career”)
BS Biochemistry, UT Austin, 2013
- Joined the Biomedical Research Computing Facility (BRCF) and Marcotte Lab summer 2017
- Also affiliated with
Daryl Barth, daryl.barth@utexas.edu
- BS Materials Science & Engineering, UC Berkeley, 2017
- Student Researcher in France and Portugal 2017 - 2018
- Research Assistant in single cell genomics, UT Southwestern 2019-2021
- 3rd year graduate student in the Marcotte Lab
Research Interests: biomaterials, developmental biology, and bioinformatics
About the Iyer Lab (where Anna learned NGS)
Dr. Vishy Iyer, PI |  |
Main focus is functional genomics
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Research methods include
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Communication
Asking questions
Feel free to ask questions any time during the instructor's lecture and demonstrations.
For online attendees, you can also post your question to the Zoom chat. We'll sometimes use breakout rooms when troubleshooting problems you run into, if so, TA Daryl Barth will assign you to one.
Getting help
Since most folks are new to the Linux command line, we expect you to run into problems! Please let us know if you're having difficulties!
Making mistakes and running into problems is key to learning the Linux command line! It is not only expected – it is encouraged 
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Conventions
If you see a block of text like this:
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ls -h |
it means, "type the command ls -h into a terminal window, hit return Enter, and see what happens".
We intend this course to offer as much self-learning as possible. Consequently, you'll find many sections like this - click on the triangle to expand them:
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Hint sections will provide you some guidance on what to do next, but will not spell it out. |
and some sections like this:
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Solution sections will contain the |
About the Iyer Lab
- Main focus is functional genomics
- large-scale transciptional reprogramming in response to diverse stimuli
- Encode consortium collaborator
- work in human and yeast
- Research methods include
- microarrays
- high-throughput sequencing (since 2007)
- especially ChIP-seq
- also RNA-seq, RIP-seq, MNase-seq ...
- we now have > 1,200 NGS datasets
- Anna's background
- BA English literature, 1978
- Commercial software development 1982 – 2005
- Joined Iyer Lab 2007 (“retirement career”)
- BS Biochemistry, 2013
- Daechan's background
- BS Biology, Seoul National University, 2008
- Ph.D Cell and Molecular Biology, UT Austin, 2014
- Baby sitting, Current
will represent one method of answering the question – but there are often many ways to skin a cat! |
Course goals
- Hands-on, tutorial style – learn by doing
- Common bioinformatics tools & file formats
- Introduce NGS vocabulary
- both high-level view and practice with specific tools
- Cover the NGS basics
- The first few things you'll do after receiving raw sequences
- raw sequence QC and preparation
- alignment to reference
- basic alignment analysis
- The first few things you'll do after receiving raw sequences
- Understand and practice required skills
- Get you comfortable with Linux and TACC – your best "frenemies"
- Make you self-sufficient enough in 5 days to become experts over time
- Show some "best practices" for working with NGS data
NGS Challenges
Diverse skill set requirements
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Large and growing datasets
NGS methods produce staggering amounts of data!
Typical dataset these days
- yeast: 5 – 20 million reads
- human: 20 – 250 million reads (~5 - 8 million for TagSeq)
- single end (SE) or paired end (PE), length 50 – 300 bases (100 or 150 typical)
The initial FASTQ files are big (100s of MB to GB) – and they're just the start.
- Organization and naming conventions are critical.
- Your data can get out of hand very quickly!
Progression of Iyer Lab datasets over time:
- 2008 – Yeast heat shock remodeling of chromatin
- 2 yeast datasets
- less than 2 million sequences
- 2010 – Allelic bias in CTCF binding
- 13 CTCF datasets from 3 GM cell lines
- ~200 million sequences
- 2012 – Transcription factor data analysis (ENCODE2)
- 32 ChIP-seq datasets gathered over 3 years (3 TFs across 11 cell lines)
- ~ 1 billion sequences
- 2013 – miRNA overexpression effects
- 42 RNAseq datasets (7 conditions)
- ~ 2.6 billion sequences
- 2014 – eQTL analysis of CTCF binding
- 52 very deeply sequenced CTCF datasets
- ~ 8 billion sequences
- 2018 – Functional analysis of glioblastoma tumors and cell lines
- nearly 500 datasets in total (ChIP-seq, RNAseq, miRNAseq, 4C, exome/genome sequencing)
- > 22 billion sequences
...