RT @conor_rossi: Yesterday our paper on the genomics of the extinct aurochs was published in @Nature! I’m so happy to see this work finally….

RT @brad_dan: Our new paper on the dynamic ancient genomic history of the aurochs is out in Nature. Well done to all, esp. Conor Rossi. Fre….

Our study on ancient Anatolian sheep 🐑 genomes 🧬 is finally out!!!. Tons of insights into the early domestication processes in Anatolia and some interesting bits to look into with further research across Eurasia. Check the paper by Damla Kaptan et al:

RT @biorxiv_bioinfo: SAFARI: Pangenome Alignment of Ancient DNA Using Purine/Pyrimidine Encodings #biorxiv_bioinfo.

RT @FSanchezQuinto: Interested in a project in the intersection of ancient DNA and Deep Learning for characterizing genetic variation? Do s….

Important note for those early adopters who downloaded the preprint version of READv2 from Github: Make sure to get the newest version, we added some fixes during the revision process (2/2).

The READv2 paper, the outcome of @masterolojist 's MSc thesis is now out 🥳: . "READv2: advanced and user-friendly detection of biological relatedness in archaeogenomics". Congrats to Erkin and everyone else involved!! .🧵 (1/2).

RT @mmerfff: Our latest preprint 👊 DeepKin: Predicting relatedness from low-coverage genomes and paleogenomes with convolutional neural net….

Overall, #SMBEbeyond has been an awesome time thanks to all attendees and especially the @SMBESat2024_TCD team for organizing

For example, @MSrigyan received the #SMBEbeyond poster prize for her current work on Tricolored blackbirds 🎉

One of the best things about attending conferences is that you get a chance to see what your former students are up to. It's great to see what @masterolojist @MSrigyan @genesandstuff have turned into . #SMBEbeyond

RT @louis_l_hote: I am delighted to share my first first-author and the first paper of the @gingerhowley lab published in Nature Communicat….

RT @gulsahhdal: Our paper about evaluating genotype imputation using Glimpse2 is published today. This was the Master thesis study of Hand….

RT @PalaeoPete: We are excited to share our new paper introducing a new tool for scrutinising #ancientDNA data - AMBER - and using this too….

Sad to miss #SMBE2024 but make sure not to miss the presentations from the lab:. @MariDehasque will present a poster on Roman sheep genomes 🐏 (13-Tue). Germán Hernández-Alonso will talk about genomic diversity, history and conservation of rock doves 🕊️ on Fri 9:50 (Las Pilitas).

Turns out ph calls are best at reproducing the general distribution while GLs correlate better in per site estimates 😕. Might not be surprising but we need to keep in mind that all estimates from low coverage data are noisy regardless of the method used, mapping bias etc. (6/6).

Since demographic inference is often based on the allele frequency spectrum, we also compared allele frequencies in 1000 genomes project individuals estimated from GLs to pseudohaploid calls and frequency estimated from SNP chip data. (5/6).

The effect of mapping bias on estimated ancestry proportions is rather small (<5%) but consistent and adjusting GLs helps to reduce (but not fully remove) the impact. GLs are versatile and have numerous downstream applications beyond ancestry proportions. (4/6).

Since some of those tools were based on genotype likelihoods (GL), we combined it with an idea we had back in 2019 about adjusting GLs for mapping bias, so we added a step of mapping to reference genomes ascertained from different populations (in- and outgroups). (3/6).

It all started with Josh wondering how us aDNA people estimate ancestry proportions, so we tried to benchmark some tools (ADMIXTURE, qpAdm, (fast)ngsadmix) using simulations. It turns out that there are quite some differences between methods. If possible, qpAdm worked best. (2/6).