Laurits Skov

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

We also found cases where hybrid decoding recovers a putative neanderthal fragment that was split in two by posterior decoding and where only half was found by viterbi decoding.

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

We recommend picking the alpha closest to the 45 degree line (ideally you want to be as close to the top right corner as possible). We call these plots Artemis plots because of the bow like shape!

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

The best alpha will depend on the specific emission and transition parameters. Also an alpha of 0.5 does not nescessaraly mark the halfway point between the two methods. There we propose a simulation approach for picking the appropriate alpha for your analyse.

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

Posterior decoding maximixes the local probability - that is the pointwise accuracy. This leads to more short fragments being recovered but also a higher false positive rate.

We ( @zeniabaek.bsky.social @moicoll.bsky.social and @asgerhobolth.bsky.social ) present a new cool way to visualize the optimal trade off for hmm decoding called Artemis plots! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1...

This part of the manuscript has to do with finding the best decoded path for a hidden markov model so let's talk the two most used: Viterbi and posterior decoding

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.

This was a great collaboration with Moisès Coll Macià, Zenia Elise Damgaard Bæk and Asger Hobolth :)

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.

This sampling approach is easy to implement and can be used for all HMMs commenly used! One could calculate what the distribution of long IBD fragments are between two ancient individuals, how much time you are in a given TMRCA state for PSMC or sample paths through the Li -Stephens copying model.

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.

You can even get close to the true fragment length distribution. Black vertical line is true mean fragment length and black curve is expected theoretical distribution. Colored dotted vertical lines are means for each decoding type

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.

Another strategy is to sample many decoded paths conditioned on the data. The benefit of this is that sometimes you find the short fragments! And instead of one decoded path you have many sampled paths from which you can calculate any summary statistic you want (with confidence intervals!)

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.

To find fragments we use is a Hidden Markov Models (HMMs) which classifies the genome into an archaic and a human state based on the SNP-density of variants not found in African genomes where there is little archaic DNA. We then "decode" the genome to find into archaic and human fragments.

Very excited to be part of two manuscripts which are now on biorxiv! arxiv.org/pdf/2504.15156 www.biorxiv.org/content/10.1... Archaic humans such as Neanderthals and Denisovans are extinct but their DNA lives on in many humans today because our ancestors met and had children with them.