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Torsten Günther Profile
Torsten Günther

@trstn_gnthr

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Population genomics, ancient DNA, domestication, human prehistory - Researcher at Uppsala University @HumanEvoUU @[email protected]

Uppsala, Sweden
Joined August 2016
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@trstn_gnthr
Torsten Günther
8 months
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….
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@trstn_gnthr
Torsten Günther
8 months
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….
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@trstn_gnthr
Torsten Günther
9 months
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:
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@trstn_gnthr
Torsten Günther
11 months
RT @biorxiv_bioinfo: SAFARI: Pangenome Alignment of Ancient DNA Using Purine/Pyrimidine Encodings #biorxiv_bioinfo.
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@trstn_gnthr
Torsten Günther
11 months
RT @FSanchezQuinto: Interested in a project in the intersection of ancient DNA and Deep Learning for characterizing genetic variation? Do s….
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@trstn_gnthr
Torsten Günther
11 months
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).
@trstn_gnthr
Torsten Günther
1 year
We are excited to release READv2, a new version of the popular tool for detecting biol relatedness in aDNA data. @masterolojist made it faster and more precise than v1 while adding features for telling apart sibs and parent-offspring + 3rd degree. 🧵(1/5).
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@trstn_gnthr
Torsten Günther
11 months
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).
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@trstn_gnthr
Torsten Günther
11 months
RT @mmerfff: Our latest preprint 👊 DeepKin: Predicting relatedness from low-coverage genomes and paleogenomes with convolutional neural net….
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@trstn_gnthr
Torsten Günther
11 months
Overall, #SMBEbeyond has been an awesome time thanks to all attendees and especially the @SMBESat2024_TCD team for organizing
@SMBESat2024_TCD
SMBE Ancient DNA Beyond Allele Frequencies
11 months
Thank you everyone! #smbeBeyond
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@trstn_gnthr
Torsten Günther
11 months
For example, @MSrigyan received the #SMBEbeyond poster prize for her current work on Tricolored blackbirds 🎉
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@trstn_gnthr
Torsten Günther
11 months
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
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@trstn_gnthr
Torsten Günther
1 year
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….
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@trstn_gnthr
Torsten Günther
1 year
RT @gulsahhdal: Our paper about evaluating genotype imputation using Glimpse2 is published today. This was the Master thesis study of Hand….
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@trstn_gnthr
Torsten Günther
1 year
RT @PalaeoPete: We are excited to share our new paper introducing a new tool for scrutinising #ancientDNA data - AMBER - and using this too….
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@trstn_gnthr
Torsten Günther
1 year
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).
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@trstn_gnthr
Torsten Günther
1 year
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).
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@trstn_gnthr
Torsten Günther
1 year
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).
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@trstn_gnthr
Torsten Günther
1 year
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).
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@trstn_gnthr
Torsten Günther
1 year
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).
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@trstn_gnthr
Torsten Günther
1 year
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).
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