1. Yonglan Zheng (yzheng3@uchicago.edu) 2017.6.10
Galaxy Hands-on Demo Step-by-step
Yonglan Zheng

2. Download five input files at Mega through web browser
human_b37_20.fasta
aligned_20.p1.fastq
aligned_20.p2.fastq
chr20_100000_ bed
indels_b37_20.vcf
.fasta, .vcf and .bam can be found at ftp://ftp.broadinstitute.org/tutorials/workshops/GATK_basic/
I converted the aligned_20.bam into two.fastq files

3. 2. Register your Galaxy account
Go to Galaxy main site
If it has some issues like file system errors you can also try Galaxy test sitehttps://test.galaxyproject.org/ which is the beta version of the Galaxy main

4. 3. Login your Galaxy account
4. Create a new history at the upper right of the page, give it a name

5. 5. Upload input files into the history
on the upper left panel,
or,
on the upper right panel
Drag and drop your files or “Choose local file”

6. 6. Select file format and data type
“Type”: fasta, fastqsanger, bed and vcf for reference genome, FASTQ files, region BED file, and known Indel VCF, respectively
“Genome”: Human Feb (GRCh37/hg19) (hg19)
Upload the files by the order showed below. Actually it does not matter, but the exact order might help you to follow this demo easily.
Click “Start”, when it is done, click “Close”. Grey – pending; yellow – running; green – completed; red – failure. You can keep adding tools without the output completed from the previous steps.

7. 7. Quick FASTQ QC
Search tool FASTQC and click it.
Select one FASTQ file, here, aligned_20.p1.fastq first, click “Execute”.
While it is pending or running, you can choose FASTQC again and apply it to another FASTQ file aligned_20.p2.fastq. These two .fastq are one pair.

8. 8. View FASTQC report
Click the eye icon to view the output

9. 9. Alignment with BWA-MEM
Search BWA-MEM in the tools, click it, choose your inputs, and execute BWA-MEM.
Select here to use the reference genome in the history instead of the build-in
Select your .fastq here
Set the read group, see next slide

10. 9. Alignment with BWA-MEM (continued)

11. 10. Restrict to a region for variant calling
Search Slice in the tools, click it, choose your inputs, and then execute.
You can refresh the history here

12. 11. Remove duplicates in the BAM Search MarkDuplicates in the tools.
If you are not sure, select “No” here

13. 12. Realigner target
Search Realigner Target Creator in the tools.
Make sure to use the reference from the “History”

14. 12. Realigner target (continued)
Use known Indels to help local realignment

15. 13. Indel realignment
Search Indel realigner in the tools.

16. 14. Variant calling
Search Unified Genotyper in the tools. You don’t need indels_b37_20.vcf here.

17. Search SnpEff in the tools. Select SnpEff galaxy v4.0.0
15. Variant annotation
Search SnpEff in the tools. Select SnpEff galaxy v4.0.0
v ✓
v ✗
Only three annotation options were selected, for simplicity

18. 16. Filtering the annotated variants
Search Select in the tools. Only look at variants with “HIGH” effect.
It is done! Cheers!
Click the eye icon to view your result.
You can also download the result.
You can visit this history anytime.

19. Good luck and enjoy your journey of NGS analysis!
17. Another practice and small test
This time, your upstream study (linkage, GWAS etc.) suggests a candidate region chr20: (hg19). You conduct NGS on one sample and aim to identify a pathogenic variant. Unluckily GATK Unified Genotyper breaks down, so you have to use another variant caller, let’s say FreeBayes.
Use the same .fasta, .fastq, and .vcf input files. Make your own .bed file for that candidate region. Start with file uploading, and then alignment, local realignment, variant calling, annotation and filtering.
Good luck and enjoy your journey of NGS analysis!