1. Using command line tools to process sequencing data
Tapio Vuorenmaa, Krista Kokki
Using command line tools to process sequencing data

2. This hands-on session:
Part 1 – Bedtools
Part 2 – DEMO: Galaxy with the command line
Part 3 – Bedtools excercises

3. Part 1: Bedtools Allows to do wide range of genomics tasks easily
Command line tool
Easy to use
 Perfect example
We’re focusing on using command line and parameters, not to tool itself
”intersect”

4. Bedtools - intersect
”Do my two features in the set overlap with each other?”
Files: “genes.bed” and “markers.bed” (in exercises)
.bed format

5. .bed format?
Flexible way to define data lines displayed in annotation track
One of the file types Genome Browser uses
Three required fields: chr, chr start, chr end
Additional fields; name, score, strand etc.
Our ”data” is simplified

6. Our ”data”
Chromosome 1.
Chromosome 2.

7. Back to intersect Question: Do my chip-seq peaks overlap?
The basic command:
bedtools intersect –a genes.bed –b markers.bed > result.bed
Optional parameters
Program
Command
First file
Second file
Redirect output (optional)

8. Optional parameters
-wa  Display the original feature for each overlap -u  Display only one (the first) overlap found. -s  Only display overlaps found on the same strand. -c  Count the number of overlaps. -v  Complement, display those which do not overlap. -S  Only display overlaps found on the opposite strand. And many more. See your bedtools cheat sheet.

9. That’s not all there’s to it
There are number of other things you can do with bedtools, such as
Coverage
Merge
Cluster

10. Part 2: DEMO: Galaxy with the command line
Step 1. .sra file into fastqc
fastq-dump NAME.sra --offset 33
Output: .fastq file
Step 2. Quality report of your data
fastqc NAME.fastq
Output: .html file
Quality conversion
(to get quality score from ASCII code)

11. DEMO: Galaxy with the command line
Step 3. Trimming (optional)
fastx_trimmer -i NAME.fastq -o TRIMMED_NAME.fastq -f 1 -l 50
Input file
Output file
First base to keep
Last base to keep

12. DEMO: Galaxy with the command line
Step 4. Quality filtering
fastq_quality_filter -i TRIMMED_NAME.fastq -o QFILT_NAME.fastq -q 10 -p 100
Input file
Output file
Minimum quality score to keep
Minimum % of bases that must have –q quality

13. DEMO: Galaxy with the command line
Step 5. Removing quality information
fastx_collapser -i QFILT_NAME.fastq -o COLPS_NAME.fasta
Input file
Output file

14. DEMO: Galaxy with the command line
Step 6. Mapping
bowtie //hg19 -f COLPS_NAME.fasta, --best -v 2 -m 3 -k 1 output.sam
Output: .sam
Genome
Query input files (f=fasta)
Result in best-to-worst order
No more than 2 mismatches
Not reporting alignments for reads having more than 3 reportable alignments
Report up to 1 valid alignments
Output in sam format

15. DEMO: Galaxy with the command line
Finally: Samtools
Genome browser doesn’t use .sam format (output from mapping).
.sam must be converted to .bam
samtools view –bS NAME.sam > NAME.bam
Output: .bam
Now you can visualize the result in Genome browser.
Sam to bam (when having header)

16. So, why the command line?
Remote access: you can easily access and operate other computers, such as the computing servers, using the command line.
Speed: Programs are (usually) controlled by parameters. Once you learn to use these commands and parameters, they are very quick to use.
Control: Using pipelining and redirection enables users to perform powerful tasks with a single line of commands.
Automation: With scripting users can create sequences of program tasks to execute automatically without further user interaction.

17. Don’t be scared of the command line!