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CREST: mapping somatic structural variation in cancer genomes with base-pair resolution

Clipping REveals STructure (CREST) algorithm uses next-generation sequencing reads with partial alignments to a reference genome to directly map structural variations at the nucleotide level of resolution. Experimental validation exceeded 80%, demonstrating that CREST had a high predictive accuracy.

References:

Documentation
Important Notes

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive
[user@cn3144 ~]$ module load CREST 
[+] Loading ucsc 373 on cn3261 
[+] Loading samtools 1.3.1  ... 
[+] Loading BLAT  3.5 
[+] Loading CREST  1.0.1 
Copy sample data from an application folder to current folder:
[user@cn3144 ~]$ cp $CREST_DATA/* . 
Run CREST on the sample data: :
[user@cn3144 ~]$ extractSClip.pl  -i tumor.bam --ref_genome $CREST_REF/hg19.fa
[fai_load] build FASTA index.
This command will produce files tumor.bam.cover and tumor.bam.sclip.txt in the current directory.

Batch job
Most jobs should be run as batch jobs.

Create a batch input file (e.g. crest.sh). For example:

#!/bin/bash
module load CREST    
cp $CREST_DATA/* . 
extractSClip.pl  -i tumor.bam --ref_genome $CREST_REF/hg19.fa
extractSClip.pl  -i germline.bam --ref_genome $CREST_REF/hg19.fa
...

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] crest.sh