The document summarizes an agenda for a Next Generation Sequencing bioinformatics workshop. It includes: 1) A review of common data formats like FASTQ and SAM/BAM used for NGS data as well as tools for working with these formats. 2) An overview of the Picard and FASTX command line tools for processing NGS data. 3) A reintroduction to the Galaxy platform for analyzing NGS data through an online tutorial. 4) Suggested steps for a typical NGS data analysis workflow including quality control, assembly, and mapping.

1. NGS Bioinformatics Workshop
2.1 Tutorial – Next Generation Sequencing
and Sequence Assembly Algorithms
May 3rd, 2012
IRMACS 10900
Facilitator: Richard Bruskiewich
Adjunct Professor, MBB

2. Agenda
Data format review (and some associated
tools)
Revisit Galaxy
Revisit data visualization

3. FASTQ
 FASTQ – FASTA “with an attitude” (embedded quality scores). Originally
developed at the Sanger to couple (Phred) quality data with sequence,
it is now common to specify raw read output data from NGS machines
in this format.
 Various flavors:
 fastq-sanger
 fastq-illumina
 fastq-solexa
Differing in the format of the sequence identifier and in the valid range of
quality scores. See:
http://en.wikipedia.org/wiki/FASTQ_format
http://maq.sourceforge.net/fastq.shtml
http://nar.oxfordjournals.org/content/early
/2009/12/16/nar.gkp1137.full
“…the Sanger version of the FASTQ format has found the broadest
acceptance, supported by many assembly and read mapping tools
…Therefore, most users will do this conversion very early in their
workflows…”
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+EAS54_6_R1_2_1_443_348
*-+*''))**55CCF>>>>>>CCCC

4. SAM/BAM
SAM– a tab-delimited text file that contains a
compact and index-able representation of
nucleotide sequence alignments
http://samtools.sourceforge.net/SAM1.pdf
http://samtools.sourceforge.net/
BAM – binary version of SAM (preferred by IGV)
I/O format of several NGS tools, see:
http://samtools.sourceforge.net/swlist.shtml
See also:
Li H.*, Handsaker B.*, Wysoker A., Fennell T., Ruan J., Homer N., Marth
G., Abecasis G., Durbin R. and 1000 Genome Project Data Processing
Subgroup (2009) The Sequence alignment/map (SAM) format and
SAMtools. Bioinformatics, 25, 2078-9.

5. http://picard.sourceforge.net/command-line-overview.shtml
http://picard.sourceforge.net/
The Picard command-line tools are packaged as executable jar files. They require Java
1.6. They can be invoked as follows:
java jvm-args -jar PicardCommand.jar OPTION1=value1 OPTION2=value2...
Most of the commands are designed to run in 2GB of JVM, so the JVM argument -
Xmx2g is recommended.

6. Getting & Running Picard…
Obtain archive using project “Download” link
Extract zip file to sensible location
Ensure that you have Java 6 on your machine
Run from command shell as indicated

7. http://hannonlab.cshl.edu/fastx_toolkit/
Linux, MacOSX or Unix only

8. Visualization of NGS Data - Standalone
http://www.broadinstitute.org/igv/

9. Visualization of NGS Data – Web Site
http://gmod.org/wiki/GBrowse_NGS_Tutorial

10. GALAXY REVISITED
2.1 Next Generation Sequencing and Sequence Assembly Algorithms

11. Learning about Galaxy
Extensive web resources available:
http://wiki.g2.bx.psu.edu/Learn/
Getting started: “Galaxy 101”
Other screencasts
Information pages about dataset management,
tool usage and data visualization
Published pages/protocols:
https://main.g2.bx.psu.edu/page/list_published

12. Logging into Galaxy @ WestGrid
https://joffre.westgrid.ca/galaxy/
Accessing the Westgrid Galaxy instance
Use your Westgrid ID (email name without @part)
to log into Joffre, e.g. if your email is
‘rbruskie@sfu.ca’, your server access id is
‘rbruskie’, and use your WestGrid password
Logging into the Galaxy instance
Once into Galaxy, you need to register (initially) or
log in (if already registered) using your username
(your full email, e.g. ‘rbruskie@sfu.ca’) and
(important!) use your WestGrid password as the
Galaxy password

13. Small issue for access through IE?

14. We will run through “Galaxy 101”
https://main.g2.bx.psu.edu/galaxy101
Try it! Ask questions along the way….

15. Some sensible steps for processing NGS data
Obtain the data (i.e. upload to Galaxy)
Assess quality of read data
Convert reads to convenient form (fastq?)
Filter out questionable data: low quality,
vector
Process to integrate
de novo assembly: Allpaths, ABySS, Velvet,
SOAPdenovo, etc., or…
Map onto reference: SAM, Bowtie, MAQ, etc.
Clean up and visualize