Sangyu Xu

Sangyu Xu

@xusangyu.com

xusangyu.com

19 followers32 following20 posts

Sangyu Xu
@xusangyu.com

The modern world is saturated with automatically collected metrics. Across science and beyond, many of us are trying to understand not merely whether a number moved, but by how much, with what uncertainty, and whether the change is large enough to matter.

Sangyu Xu
@xusangyu.com

The bootstrap-enabled uncertainty quantification is especially transparent. Unlike error bars derived from theoretical distributions, you just resample your data to form the interval empirically.

Sangyu Xu
@xusangyu.com

What delights me most is how far the idea travels. I keep meeting the same problem far outside neuroscience and biology: how much did a model improve, how large was a drug's effect, what should we make of a shift in the numbers recorded from our own bodies?

Sangyu Xu
@xusangyu.com

The idea is simple. "Is there a difference?" is almost never the question we actually care about. How big is it? How sure are we? Does it matter? DABEST answers those directly, guiding the eyes towards the quantified effect sizes and confidence intervals instead of an asterisk(or 2 or 3 asterisks).

Sangyu Xu reposted

David Colarusso
@davidcolarusso.com

Replying to @davidcolarusso.com

I go back to the office on Monday, and as a last gasp of vacation I took some time on my flight home yesterday to spruce up my other website sadlynothavocdinosaur.com, including updating this preview image. I mean, that T elevator is so a TARDIS.

sadlynothavocdinosaur.comSadly Not, Havoc Dinosaur: A website by David Anthony ColarussoMy name is David Colarusso. I founded and co-direct Suffolk University Law School's Legal Innovation & Technology (LIT) Lab. By training I'm an attorney & science educator. By experience, I'm a data s...

Sangyu Xu reposted

Climate, Ecology, War & More: Dr. Glen Barry BigEarthData.ai
@bigearthdata.ai

Getting over ANOVA: estimation graphics for multi-group comparisons ->Nature | More info at BigEarthData.ai

nature.comGetting over ANOVA: estimation graphics for multi-group comparisonsDABEST is available in both Python and R. The Python package, DABEST-python, is hosted on PyPI, and its source code can be found on GitHub at https://github.com/ACCLAB/DABEST-python. A tutorial for the Python package can be found at https://acclab.github.io/DABEST-python/tutorials/. The R variation, dabestr, is available on CRAN (https://cran.r-project.org/web/packages/dabestr) and similarly has its source code accessible on GitHub (https://github.com/ACCLAB/dabestr). A tutorial for the R package is available at https://acclab.github.io/dabestr/. Both repositories are released under the Apache-2.0 license. In addition, https://www.estimationstats.com provides an online user interface and performs all calculations using DABEST-Python. The Python notebook used to generate Fig. 1 and Supplementary Figs. 1–3 has been deposited to Zenodo (https://doi.org/10.5281/zenodo.18426513). This study was funded by grants from the Ministry of Education of Singapore (MOE): Z.L., R.Z., K.L., S.H., L.Z.W., Y.L., F.L. and A.R.C.G. were supported by 2022-MOET1-0001; J.A. was supported by FY2023-MOET1-0001; Y.M. was supported by a President’s Graduate Fellowship, MOE-T2EP30222-0018 (Research Scholarship) and MOE-T2EP30223-0009; N.M.L. was supported by Research Scholarships MOE2019-T2-1-133 and MOE-T2EP30222-0018; H.C. was supported in part by MOE (T2EP20223-0010) and the National Medical Research Council of Singapore (NMRC, CG21APR1008); S.X. was supported by the A*STAR Scientific Scholars Fund and NMRC (MOH-OFYIRG20nov-0051); A.C.-C. was supported by MOE (FY2022-MOET1-0001); A.C.-C. was also...
Sangyu Xu
@xusangyu.com

A hungry fly doesn’t just eat more: it moves differently, sips differently, goes to different places. How do we profile “hunger” in the most holistic manner we can?

bioRxiv Neuroscience@biorxiv-neursci.bsky.social

Contextualized phenovectors reveal a Drosophila serotonergic circuit controlling satiety https://www.biorxiv.org/content/10.64898/2026.07.01.735755v1

Sangyu Xu
@xusangyu.com

A hungry fly doesn’t just eat more: it moves differently, sips differently, goes to different places. How do we profile “hunger” in the most holistic manner we can?

bioRxiv Neuroscience@biorxiv-neursci.bsky.social

Contextualized phenovectors reveal a Drosophila serotonergic circuit controlling satiety https://www.biorxiv.org/content/10.64898/2026.07.01.735755v1

Sangyu Xu
@xusangyu.com

Using this method, we show that tryptophan hydroxylase expressing neurons in Drosophila bidirectionally regulate hunger-satiety state transitions, mainly through the population in the ventral nerve cord and possibly through Sut2 signaling.

Sangyu Xu
@xusangyu.com

A hungry fly doesn’t just eat more: it moves differently, sips differently, goes to different places. How do we profile “hunger” in the most holistic manner we can?

bioRxiv Neuroscience@biorxiv-neursci.bsky.social

Contextualized phenovectors reveal a Drosophila serotonergic circuit controlling satiety https://www.biorxiv.org/content/10.64898/2026.07.01.735755v1

Sangyu Xu
@xusangyu.com

We believe that by first defining a benchmark ground truth from natural starvation experiments, and second matching phenovectors from intervention experiments to the ground truth, we uncover the most faithful movers of hunger-satiety transitions.

Sangyu Xu
@xusangyu.com

Our new preprint out! We cloned a fly codon-optimized LSSmScarlet3 which glows red under 920 nm IR and allows simultaneous imaging with GCamps. Perfect for a structural marker in in vivo imaging with a simplified laser setup, and opens up possibilities for many other applications!

bioRxivpreprint@biorxivpreprint.bsky.social

Long-Stokes-Shift mScarlet3 as a Structural Marker for Two-Photon Imaging https://www.biorxiv.org/content/10.64898/2026.04.12.718060v1

Sangyu Xu reposted

David Colarusso
@davidcolarusso.com

Replying to @davidcolarusso.com

We finished! On the way out the door this morning, the kids and I attached the last piece of our #LEGO Enterprise. Fun was had by all.

Sangyu Xu
@xusangyu.com

A fan of the DABEST package but want to do some multi-group analysis? Our expanded DABEST 2.0 does just that. Rethink NHST-based dichotomy and estimate the actual effect sizes with confidence intervals! Find out more in our new preprint.

bioRxiv Bioinfo@biorxiv-bioinfo.bsky.social

Getting over ANOVA: Estimation graphics for multi-group comparisons https://www.biorxiv.org/content/10.64898/2026.01.26.701654v1

Sangyu Xu reposted

Bob C-J and Geoff Cumming
@thenewstats.bsky.social

So excited to see DaBest 2.0 is out: get bootstrapped estimation statistics for simple through complex designs, all with beautiful visualization, available in R and Python. Check it out! Pre-print describing new features for complex designs: www.biorxiv.org/content/10.6... #stats

biorxiv.orgGetting over ANOVA: Estimation graphics for multi-group comparisonsData analysis in experimental science mainly relies on null-hypothesis significance testing, despite its well-known limitations. A powerful alternative is estimation statistics, which focuses on effect-size quantification. However, current estimation tools struggle with the complex, multi-group comparisons common in biological research. Here we introduce DABEST 2.0, an estimation framework for complex experimental designs, including shared-control, repeated-measures, two-way factorial experiments, and meta-analysis of replicates. ### Competing Interest Statement The authors have declared no competing interest.

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