Here is s short a presentation about SV-plaudit on YouTube (2m 16s) GIGGLE

Links:

Detection structural variants (SVs) is hard, and automated filters still struggle to differentiate between true positives and false positives. While the human eye is quite good at spotting spurious SV calls, curating more than a handle full of calls with current visualization tools is clumsy and error-prone.

SV-plaudit aims to scale manual inspection to thousands of SVs so that you can curate every variant in your call set. We accomplish this with a visualization method that reduces the time required to evaluate and SV to seconds and a cloud-based scoring system that manages the input from many users.

Checkout out the setup video and the following commands to set up your AWS environment and deploying an example SV-plaudit project. Complete details are on the GitHub site.

Get the code:

git clone --recursive https://github.com/jbelyeu/SV-plaudit.git
cd SV-plaudit

Get sample data (this could take 20 or more mintues, depending on network speed):

samtools view -b ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/phase3/data/NA12892/high_coverage_alignment/NA12892.mapped.ILLUMINA.bwa.CEU.high_coverage_pcr_free.20130906.bam 22 > NA12892.22.bam
samtools view -b ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/phase3/data/NA12891/high_coverage_alignment/NA12891.mapped.ILLUMINA.bwa.CEU.high_coverage_pcr_free.20130906.bam 22 > NA12891.22.bam
samtools view -b ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/phase3/data/NA12878/high_coverage_alignment/NA12878.mapped.ILLUMINA.bwa.CEU.high_coverage_pcr_free.20130906.bam 22 > NA12878.22.bam
samtools index NA12878.22.bam
samtools index NA12891.22.bam
samtools index NA12892.22.bam
bcftools view -c 1 -s NA12878 ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/phase3/integrated_sv_map/ALL.wgs.integrated_sv_map_v2.20130502.svs.genotypes.vcf.gz > NA12878.22.vcf

Generate an image for each SV:

mkdir sv_imgs
Samplot/src/samplot_vcf.sh -S Samplot/src/samplot.py -o sv_imgs -v NA12878.22.vcf NA12878.22.bam NA12891.22.bam NA12892.22.bam

Stage the AWS environment and upload the data:

python PlotCritic/setup.py -p NA12878_trio_22 -e ryan@layerlab.org -a YOUR_AWS_ACCESS_KEY_ID -s "YOUR_AWS_SECRET_ACCESS_KEY"
python upload.py -d sv_imgs -c PlotCritic/config.json

At this point you will get an eamil with the URL to the scoring web site and temporary password for your administrator account. When you first signin you need to reset your passowrd, then you can invite other users and begin evaluating varaints.

Once scores have been collected, results can be retrieved as either a tex file or annotated VCF.

python PlotCritic/retrieval.py -c PlotCritic/config.json > retrieved_data.csv
python annotate.py -s retrieved_data.mod.csv -v NA12878.22.vcf -a NA12878.22.score.vcf -o mean -n 1,0,1