#genotyping
Live, measured metrics for the hashtag #genotyping from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #genotyping
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 14:07 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 14:07 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 14:07 UTCEverything below is measured over the latest 16 public posts (spanning ~25174 hours).
Posting hours (UTC) — busiest: 15:00
Languages: English (16)
Avg boosts / post: 0.9
Top of the latest posts
And it’s finally here 🥳 {resurface} my #rstats package for imputing missing genotype allele frequencies, such as those from pooled samples or populations. Stems from some scripts I wrote nearly 10 years ago, which I can now finally say is
With phased/haplotype-aware genomes becoming more frequent I'm Curious 🤔 to hear from others how you have been handling SNP/variant calling against them 🧬 Are you sacrificing heterozygous calls and aligning to all haplotypes, or only usin
🧬🌿 axiomFP.py a software for visual ploidy and quality assessment of Axiom SNP array data https://doi.org/10.1093/insilicoplants/diaf015 #genotyping #PlantScience
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/genotyping