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Running Analysis on Multiplexed Data with different helper/rep-cap plasmids #9
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Hi @gfill88 Currently, to run multiple samples they will all have to use the same parameters, such as helper, rep_cap etc. If this is something you will be doing a lot, we could consider adding parameters per sample via the sample sheet. Thanks, Neil |
Hi Neil, Thank you for your quick reply. Yes, this is something that my lab group plans on doing often. We have many different rAAV that we would like to validate using ONT sequencing, so having the ability to process a multiplexed dataset that has different helper, repcap and transgene references would be amazing! If this is might be a doable addition to the pipeline, please let us know. We are happy to help in any way-- testing the pipeline etc. Thank you so much for considering this additional parameter-- it would be instrumental to our lab group! Gina |
Hi @gfill88 We will be adding this functionality to the workflow. I'm not sure if it will be in next release or not, but I will let you know when it does get released. Thanks, Neil |
Hi Neil, This is great news! My team and I are thrilled to be able to use this functionality. It will be immensely helpful for our work. We look forward to trying it out as soon as it is available! Thank you for considering our request and making it happen! All the best, Gina |
Thanks. Will let you know when it's ready Neil |
Ask away!
Hello,
I ran a prepared library of 9 rAAV samples on a MinION flowcell and would like to use the wf-aav-qc workflow to analyze the fastq data. I have successfully used the workflow to analyze one sample at a time but am interested in doing a "bulk" analysis of the 9 barcoded samples. I used MinKnow to bin the data and currently have the fastq files in a directory containing one level of sub-directories that contain the fastq files for each identified barcode (fastq option iii in the workflow manual).
All of the 9 samples will have the same host reference, however, the helper, rep-cap and transgene plasmid reference sequences will be different for each of the samples. Is there any way to run the workflow for multiplexed data with different references or would I need to run the workflow on each independent fastq dataset (i.e. run 9 separate analyses)?
Thank you!
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