-
Notifications
You must be signed in to change notification settings - Fork 0
Description
Hi @J35P312
I am trying to identify SV (translocations mainly) in patients with know translocations. I am setting up the pipeline with a patient with t(14:18) and I have a single-cell bam file (2000 cells) which I split by read-groups (cell ident), getting 2000 individual bam files.
I took one individual bam (corresponding to an individual cell seq) to test your tool and even though I got the expected results derived for the low coverage and probably other calculations of your algorithm, I have been able to detect the translocation!!
CHROM=chr14 | POS=106329985 | ID= SV_2_1 | REF= N | ALT= N[chr18:60793513[ | Qual= . | Filter=Ploidy | INFO= SVTYPE=BND;CIPOS=0,0;CIEND=0,0;COVA=0.0;COVB=39.7400016784668;LFA=13;LFB=13;LTE=13;OR=0,0,0,13;ORSR=0,0;QUALA=0;QUALB=60 | FORMAT= GT:CN:DV:RV:DR:RR | AACAACCTAGTGATGTGC-1=1/1:.:13:0:0,75:0,0
I was thinking in to use your tool to loop across all the 2000 bams, merge them, and extra info from it, at least, to know which cells carry each translocation (mainly the t(14:18) ).
Also, How can I interpret the translocation breakpoints and the ALT, because probably is not getting the mate break pair in the chr18.
What do you think about these results and the best way to tune your tool to squeeze my data in optimal conditions.
In addition, I got more output files than the described in your user guide; output.ploidy.tab, output.sample.bam(3.5GB), output.signals.tab, output.vcf, and output.wig
Thank you so much!!!