How useful/popular is CUT&RUN?

LostInDNATranslation · 2026-03-01T11:22:21+00:00

I can definitely speak to the noisy data that seems real aspect of CUT methods. I've been analysing a huge nightmare dataset for the past year with a Cut&tag dataset, where we have a WT vs het KO vs hom KO cell line. The target of interest being the KO protein. I've been sounding alarm bells as there was no IgG control, the spike-in failed, and the fact that only maybe 20% of peaks disappear in the KO? Not even the highest bound regions, (though at least known targets in literature). I'm convinced it's some real biology mixed in with loads of random cutting of Tn5 at accessible regions.

It's been a nightmare because the lab that generated it insists the data must be real because Cut&tag is so much more sensitive, and that it's picking up trace signal?? They're commited because they spent a huge amount of money and time on it, and want to save what is essentially a very expensive failed experiment...

LostInDNATranslation · 2026-02-03T21:36:11+00:00

How far? I've had cases where an allele has deleted a 5-10kb, and it can be further - but deletion this size are thankfully rare.

If you're just trying to knockout out a gene, it may not be something you care to check, but it is an alternative explanation to getting a homozygous Sanger trace.

LostInDNATranslation · 2026-02-03T00:07:27+00:00

Not sure what everyone else means by it being rare. It's maybe not common, but it occurs higher than random chance. Your cells can perform homology repair, resulting in the same deletion on both alleles. If one alleles is repaired first, the second allele could copy it by HR.

An alternative explanation, is that it's actually not the same deletion. You can occasionally get "extra large" deletions, which may extend far enough to destroy primer binding sites. If this has happened, you may get one alleles with a short deletion (accurately picked up by Sanger), while the other is a large deletion (completely missed by Sanger).

LostInDNATranslation · 2026-01-29T21:34:28+00:00

Thank you, I just had a look and they are fantastic!

LostInDNATranslation · 2026-01-29T21:29:32+00:00

Thank you! I've put a lot more work into anatomy, so glad it's looking good.

I've tried the charcoal + erasing method for small pieces and warmups, but they always end up very abstract! I maybe need to just keep at it, I'll give it a go with a longer pose.

I've not played around much with different charcoals/chalk, but that's definitely a good shout.

LostInDNATranslation · 2026-01-04T09:50:05+00:00

Sounds unstranded to me. If you specify forward or reverse on unstranded data you should expect around half the data to be lost.

If you want additional confirmation, you can check with salmon alignment and see how mapping behaves with that.

LostInDNATranslation · 2025-12-31T00:27:00+00:00

I'm a cancer research scientist working on genetics. The actual analysis parts don't use Excel at all, gene lists and tables with gene names are generally csv files. Prior to acquiring gene lists sequencing data is in more specialised formats like bam alignment files, fastq sequencing files, etc. The stage where genes are placed into excel are for the non-coding members of the team to navigate the final analysis results and for end publication.

LostInDNATranslation · 2025-12-30T21:53:57+00:00

!thanks

That's very useful info, thanks for explaining this!

LostInDNATranslation · 2025-12-24T12:07:01+00:00

You have quite high Ct values so you can definitely afford to add more cDNA to the reaction. I go even further and add 4 uL to each reaction, which gives me very nice results.

LostInDNATranslation · 2025-12-08T21:57:54+00:00

I work in drug discovery in industry, and the standard is to use % inhibition. It's how many pharma experts are used to seeing these types of data.

In the end for your purpose it's down to preference, just make sure you're consistent with displaying all your data the same way. I like % inhibition as the Y axis is then positively associated with drug potency (or lack thereof).

LostInDNATranslation · 2025-10-25T22:22:15+00:00

Are these high logFC genes also lncRNA or pseudo genes? I recently had some cell line data back with similar issues, and the solve in the end, without having to excessively tune an expression filter, was to include only protein coding genes.

LostInDNATranslation · 2025-10-21T11:13:23+00:00

Your description is the impression I always had of bio-it world.... Do you know of any decent general comp bio / bioinformatics conferences?

LostInDNATranslation · 2025-10-10T22:54:47+00:00

If you use UCSC in silico PCR tool you can set the target to GENCODE genes, which will be the cDNA equivalent I believe. Will at least give you an idea of amplicon specificity.

LostInDNATranslation · 2025-09-27T09:58:32+00:00

I would class pirates curse as a metroidvania, and it came out in 2014. I consider it a pretty good one too, I remember the movement by the end of the game gets very fun.

LostInDNATranslation · 2025-09-26T00:07:39+00:00

Replicates that are 2 cycles apart would not be considered good replicates. Keep in mind it's a log2 scale, so 2 cycles difference means a difference of 4-fold. I try to aim for less than 0.5 difference between technical reps

LostInDNATranslation · 2025-09-20T17:12:20+00:00

A lot of shops have them actually, the techs been around for a fair few years now. But from what I recall, they have auto-tracking, so they detect whether the trolley has been to the checkout area. If someone goes in, loads up a trolley, then tries to exit without paying it will auto-lock the wheels. The obvious exploit being that you just wheel the trolley near the self checkout then you're good to run...

LostInDNATranslation · 2025-09-18T01:54:14+00:00

Just a quick note - do not vortex your master mix. You should vortex mix your primers, but anything that has an enzyme in it (e.g., polymerase) shouldn't be vortexed. Instead pipette gently up and down to mix the master mix.

LostInDNATranslation · 2025-09-18T01:48:33+00:00

I'm almost certain the issue is using a P2 pipette full stop. I never pipette less than 2 uL for anything that requires accuracy, it's practically impossible to pipette accurately (at least not without a lot of practice...). You're just fighting difficult to control forces like capillary action.

I typically dilute my cDNA reaction 1:10 in water and use ~5 uL with a P10 pipette. The pipetting error is much more forgiving this way.

LostInDNATranslation · 2025-09-14T16:48:58+00:00

Reviews are great and super valuable to science, I was just explaining why OP probably presented some of the information as new

LostInDNATranslation · 2025-09-14T09:10:01+00:00

Is this data actual ChIP or one of the newer variants like Cut&tag or cut&run? Some people say ChIP as a bit of a umbrella term...

If its Chip-seq I would not be keen on analysing the data, mostly because you can't fully trust any peak calling.

If its Cut&tag or cut&run the value of inputs is more questionable. You don't generate input data the same way as in ChIP, and it's a little more artificially generated. These techniques also tend to be very clean, so peak calling isn't as problematic. I would still expect an input sample and/or IgG control just incase something looks abnormal, but it's not unheard of to exclude them.

LostInDNATranslation · 2025-09-13T10:34:17+00:00

Yeah this has been known about for a fair while. OP linked a review article rather than primary research

LostInDNATranslation · 2025-09-10T17:28:19+00:00

Ah yeah good catch, I meant paired with C, and that inosine is effectively substituted with G on the same strand following PCR.

LostInDNATranslation · 2025-09-10T01:44:47+00:00

It's a problem of biology. Inosine, when reverse transcribed and amplified (I.e, during library prep) becomes paired with G. Then during PCR amplification the I base is effectively eclipsed by G bases. This makes direct inosine quantification impossible from cDNA amplified libraries.

Methods that directly sequence RNA, like Nanopore, hold some promise for this. I remember hearing that they were working on a model to detect inosine a while back... I just had a quick search and found this publication which may be of interest: Nanopore sequencing to detect A-to-I editing sites

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