Day 3. Data Formats and Visualization

A large fraction of biological science in these days involves analysis of genomic data.

There are many de facto standards for representing genomic data, including but not limited to, FASTA, FASTQ, SAM/BAM, VCF, GTF, and BED formats. The ability to read and manipulate data files stored in these formats is one of the key skill sets needed for genome scientists.

Effective visualization of the genomic data and its analysis outcome is a key component for successful communication in the research community handling a large amount of genomic data.

Today, we will learn the widely used genomic data formats and practice how to read and manipulate the data in these formats. We will also learn the basics of data visualization with practice on real data.

Schedule:

Instructors:

Hyun Min Kang (HMK)
Jacob Kitzman (JK)

Topics:

I) Mini-Practice : FASTQ File Manipulation [1:15 hr] HMK

• Introductory Slides - Getting Started with FASTQ Files
• Exploring FASTQ files in UNIX

—- Coffee Break [15 mins] —

II) Lecture : Overview of Genomic Data Formats and Conversions [0:45 hr] JK

• Slides - Genomic Data Formats

III) Mini-Practice: Select a subset of variant/genotype calls [0:45 hr] JK

• Downloading a VCF file
• Selecting and manipulating variants and genotpye data

—- Lunch Break [1 hr] —

IV) Practice : Analysis with Genomic Data Formats [1:15 hr] HMK

• Understanding how to access FASTA files
• Accessing aligned sequence reads in SAM/BAM format
• Representing genes and transcripts using GTF and genePred format
• Working with BED files

—- Coffee Break [15 mins] —

V) Visualization: Overview and Practice [1:30 hr] JK

• Data visualization for exploratory analysis
• Useful plotting links
• ipython notebook - basic plotting
• ipython notebook - read counts, X vs autosomes

—- End/Wrap-Up —

Reference material

Referene Commands and Glossary