Are you interested in doing a PhD in Copenhagen? Interested in studying Neanderthals and Denisovans which live on in our genomes?
Than you are more than welcome to apply to join my group starting Jan 2026 :)

candidate.hr-manager.net/ApplicationI...

Please reach out if you have any questions!

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.

In practice this hybrid decoding has the highest accuracy when it comes to intermediate sized fragments. For short fragment posterior decoding is best and for long fragments viterbi is best.

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!

If you simulate data from your emission and transition parameters you can calculate point wise accuracy/joint posterior probability and sensitivity/specificity plots for each alpha and pick the best one!

If only there was a way to have your cake and eat it too! Inspired by previous work we propose a weighted mean of posterior and viterbi decoding controlled by a parameter alpha. When alpha = 0 you get posterior decoding and when alpha = 1 you get viterbi. When alpha is intermediate you get a mix.

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 show that our estimates of Neanderthal ancestry is consistent with f4 ratio estimates and we recover the signal of different archaic fragment length distributions across continental groups! We explored the explanations for this signal previously (www.nature.com/articles/s41...)

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

We show that by sampling hidden state sequences you can accurately recover summmary statistics (black dotted line) such as: How much of our genome is archaic? How many archaic fragments of DNA is there? How long is the longest fragment? You can even do it analytically! (red curve)

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!)

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 (and a bit nervous) to announce that I will be hiring two Postdocs for my new group(!) in Copenhagen to study the Neanderthal and Denisovan DNA which survives in present-day humans. Retweet will be much appreciated :)

Link for application:
candidate.hr-manager.net/ApplicationI...