Thomas Yssing Michaelsen

[Mads Albertsen @MadsAlbertsen85]

Last week I gave a "behind the scenes" public lecture on how we established the national surveillance of SARS-CoV-2 variants in Denmark - and how it helped to inform key decisions of the pandemic response in Denmark https://t.co/HsfavLoZ2v 1/2

[Lior Pachter @lpachter]

It's time to stop making t-SNE & UMAP plots. In a new preprint w/ Tara Chari we show that while they display some correlation with the underlying high-dimension data, they don't preserve local or global structure & are misleading. They're also arbitrary.🧵https://t.co/XkAOTKlOcs

[Rasmus Kirkegaard @kirk3gaard]

Det var ikke kun i laboratoriet at det gik hurtigt da @MadsAlbertsen85 fyrede op for analyse af #COVID19 genomer i DK. Kæmpe indsats af @CLAAUDIA_AAU teamet gjorde det muligt at få den nødvendige computerkraft på rekord tid. #infrastruktur #dkvid #dkpol #dkhealth

[Marc Stegger @MarcStegger]

Today @SSI_dk uploaded ~1,300 #SARSCoV2 genomes to @GISAID that were sequenced over the weekend. Additionally, ~2,500 previously sequenced genomes were also uploaded today. Combined, we are approaching 30K genomes that have been made available from SSI within the last 2 months.

[Marc Stegger @MarcStegger]

Another 4,000 COVID genomes from Denmark were just uploaded by @SSI_dk to GISAID

[Mads Albertsen @MadsAlbertsen85]

Our new pre-print offers a guided tour to the teams and the immense amount of data that was used to inform the pandemic response in Denmark to lineage B.1.1.7 (alpha) - a thread - 1/n: https://t.co/n6tWrPBbWQ

[Thomas Yssing Michaelsen @TYMichaelsen]

For introductions with travel history we compared the country of travel to what was inferred from the phylogenetic analysis. These only matched 27% of the time, highlighting the limitations of available genomic data, which is still biased both geographically and temporally. [7/7]

[Thomas Yssing Michaelsen @TYMichaelsen]

Introduction and transmission of SARS-CoV-2 B.1.1.7 in Denmark is live on @medrxivpreprint 🙌 Huge thanks to all in #DCGC for making this study possible! 🙏 Key findings below 👇https://t.co/bG1fOslnig

[Thomas Yssing Michaelsen @TYMichaelsen]

The majority of introductions were into the Capital region (which is also the most populous). From here, B.1.1.7 spread to other Danish regions. [6/7]

[Thomas Yssing Michaelsen @TYMichaelsen]

New sequences mostly from May. including ~70 B.1.1.7+E484K, ~20 B.1.617.2, 1 P.1, 2 B.1.351

[Thomas Yssing Michaelsen @TYMichaelsen]

Happy 100K anniversary to #DCGC! 🙌 Just started uploading ~5500 sequences --> Denmark will have >100K sequences on @GISAID soon. Hats off to the lab-people at @aauengineering and people at @SSI_dk for achieving this!

[Thomas Yssing Michaelsen @TYMichaelsen]

Also updated stats, here: https://t.co/dqf0ZGHRa4

[Thomas Yssing Michaelsen @TYMichaelsen]

Weekly @GISAID upload from #DCGC: ~5700 new sequences from first-half of May, incl. ~20 B.1.617.2, ~10 B.1.351, and ~80 B117+E484K.
Also updated the DK statistics page with data until 19 May: https://t.co/dqf0ZGHRa4

[Thomas Yssing Michaelsen @TYMichaelsen]

Weekly @GISAID upload from #DCGC: ~5300 sequences, with some interesting ones including one P.1, one B.1.351, and four B.1.525. @aauengineering @SSI_dk

[Thomas Yssing Michaelsen @TYMichaelsen]

Besides a ton of B.1.1.7 it includes ~500 B.1.525, ~80 B.1.351, and a handful P.1

[Thomas Yssing Michaelsen @TYMichaelsen]

So happy to resume the weekly @GISAID upload of DK covid19 sequences from #DCGC! 🙌Some ~36,000 sequences, covering the backlog since early March + historical sequences from late 2020.