Hprc banner tamu.png

Difference between revisions of "SW:Delly"

From TAMU HPRC
Jump to: navigation, search
(Delly)
(Delly)
 
Line 6: Line 6:
 
Delly is an integrated structural variant (SV) prediction method that can discover, genotype and visualize deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends, split-reads and read-depth to sensitively and accurately delineate genomic rearrangements throughout the genome. Structural variants can be visualized using Delly-maze and Delly-suave.
 
Delly is an integrated structural variant (SV) prediction method that can discover, genotype and visualize deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends, split-reads and read-depth to sensitively and accurately delineate genomic rearrangements throughout the genome. Structural variants can be visualized using Delly-maze and Delly-suave.
  
  module load Delly/0.8.1-intel-2018b
+
  module spider Delly
  
 
Delly primarily parallelizes on the sample level. Hence, OMP_NUM_THREADS should be always smaller or equal to the number of input samples.
 
Delly primarily parallelizes on the sample level. Hence, OMP_NUM_THREADS should be always smaller or equal to the number of input samples.
  
If you have 5 samples, for example, you would use the following in your job script along with the appropriate #BSUB values:
+
If you have 5 samples, for example, you would use the following in your job script along with the appropriate #SBATCH values:
  
 
  export OMP_NUM_THREADS=5
 
  export OMP_NUM_THREADS=5
  
 
[[ Category:SW ]] [[ Category: Bioinformatics ]]
 
[[ Category:SW ]] [[ Category: Bioinformatics ]]

Latest revision as of 09:57, 7 October 2021

Delly

GCATemplates available: ada

Delly homepage

Delly is an integrated structural variant (SV) prediction method that can discover, genotype and visualize deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends, split-reads and read-depth to sensitively and accurately delineate genomic rearrangements throughout the genome. Structural variants can be visualized using Delly-maze and Delly-suave.

module spider Delly

Delly primarily parallelizes on the sample level. Hence, OMP_NUM_THREADS should be always smaller or equal to the number of input samples.

If you have 5 samples, for example, you would use the following in your job script along with the appropriate #SBATCH values:

export OMP_NUM_THREADS=5