Chris Fields

Just a small note, there are different methods for spike-in norm that should be considered, for example: https://github.com/hbctraining/Intro-to-ChIPseq-flipped/blob/main/lessons/spikeIn_normalization.md

I'm not sure if there has been any input on this, but we have several ChIP-Seq projects that have biological reps, so having some way to keep track of these...

In the short term, couldn't replicates be captured when checking the sample sheet, then used downstream? Around this spot: https://github.com/nf-core/chipseq/blob/51eba00b32885c4d0bec60db3cb0a45eb61e34c5/bin/check_samplesheet.py#L80

> The `check_samplesheet.py` script has been already updated to get this information in `dev` in #349 but the IDR is not yet implemented. Yep, missed that. I definitely like having...

We have found much the same and pretty much stick with 99.9% consensus CCS calls, though would be good to hear @benjjneb 's thoughts; I'm also curious whether DeepConsensus calls...

Just a quick note: I don't use QIIME2 primarily so I have better control on the data processing steps. Simple before/after numbers don't give enough definition to resolve the problem,...

Yes, super odd. As a contrast, here is a recent run we have from a Sequel IIe run (CCS calls at 99.9%) which worked wonderfully: I'd have to go back...

@nhg12 They likely gave you either: * The 99% consensus calls, or * An all-inclusive run with all reads that needs to be filtered (and in the latter case they...

> Do you mean the read score in this file? this is one of the reports as I the other data is too big i cant share it here It...

@maxulysse you are awesome for taking this one, we're about to get this running for some of our projects. **EDIT**: just to add, we're not using TNseq/TNscope for this one...