Yang Chen

PhD student at @UCSDBMS in the @KnightLabNews and Gallo labs, @UWMadison alum. Skin microbiome and bioinformatics.

[Yang Chen @yangchen4379]

New paper from the Gallo and Knight labs! We demonstrate how the skin-gut axis also occurs in the reverse way: skin altering gut microbiome! https://t.co/go094GkOfr[…]tm_term=null&utm_campaign=CONR_JRNLS_AWA1_CN_CNPL_0034V_STKRE @KnightLabNews

[Yang Chen @yangchen4379]

Good times at the Society for Investigative Dermatology Conference @SocInvestDerm in Dallas, TX this past week! #skinmicrobiome #dermatology

[Kareem Carr, Ph.D. @kareem_carr]

Now that Twitter is 𝕏, I vote we rename stats twitter to ℝ.

[Yang Chen @yangchen4379]

Excited to share a new paper from the Gallo lab I had the opportunity to be a part of during my rotation last year! We find that Cutibacterium acnes isolates with a linear plasmid contribute to skin inflammation. https://t.co/1YPQApzNwS

[Selçuk Korkmaz @selcukorkmaz]

Why We Use p<0.05

🔹 Ever wondered why scientists often use p<0.05 as the threshold for statistical significance? Let's dive into its history, implications, and alternative approaches.

🔹 The p<0.05 threshold can be traced back to Sir Ronald A. Fisher in the 1920s. He suggested the 5% level as a convenient boundary for significance. However, it's important to note he never intended for it to become a rigid rule.

🔹 The p value tells us the probability of obtaining our observed results (or more extreme) if the null hypothesis is true. So, p<0.05 implies there's less than a 5% chance our results happened due to random variation alone.

🔹 However, there are critiques. Relying solely on p<0.05 has led to "p-hacking" - tweaking experiments to achieve this threshold. It's also been implicated in the replication crisis, where many scientific studies couldn't be reproduced.

🔹 So, is p<0.05 the correct way to test a hypothesis? Well, it's a tool. When used correctly and with understanding, it can provide valuable insights. But, like any tool, it has limitations.

🔹 Some suggest a more flexible approach:
•Using different thresholds depending on the field or study.
•Looking at effect sizes alongside p-values.
•Emphasizing confidence intervals to provide a range of plausible values.

🔹 Bayesian statistics is another approach. Instead of frequentist's p-values, it provides a direct probability statement about the parameter in question using prior information and observed data. This can sometimes offer a more intuitive understanding.

🔹 In conclusion, while p<0.05 has historical significance and is widely used, it shouldn't be the sole determinant of a study's validity. Science is ever-evolving, and so should our methods and understanding of data interpretation.

🔹 As always, critical thinking is key! Don't just take p<0.05 at face value. Dive deeper, understand the context, and consider alternative methods when interpreting results.

#DataScience #Statistics

[Daniel McDonald @mcdonadt]

@KnightLabNews (@UCSDMedSchool / @UCSDJacobs) is excited to announce a new release of Greengenes in @NatureBiotech (https://t.co/fwYB8CPd2y). With this release, we provide a single taxonomy and phylogeny unifying 16S and shotgun metagenomic analyses!

A thread (1/n)

[Johannes Köster (@johanneskoester.bsky.social) @johanneskoester]

#snakemake 7.30 has been recently released. We have massively improved the profile support (Snakemake's way of defining default settings). (1/n)

[Nature Biotechnology @NatureBiotech]

How the Monty Hall problem is similar to the false discovery rate in high-throughput data analysis - @jsb_ucla https://t.co/XO7jKwDnA4

[Ruben Dario Palacio, Ph.D. @rdpalacio]

Science is hard.

Good research makes you feel stupid.

You're inadequate for the task at hand.

How else would it be? You're pushing the boundaries of knowledge.

Get used to it. This process is immensely rewarding.

[Yang Chen @yangchen4379]

We just published a review paper on the skin microbiome! Check it out here: https://t.co/7qRrLjvLNo

[UC San Diego Health Sciences @UCSDHealthSci]

Yang Chen (@yangchen4379) describes recombination, one way viruses like SARS-CoV-2 can pick up new genetic changes, and how scientists detect recombinant viruses — work she did as part of her @NIH post-baccalaureate project 🧬
Full video: https://t.co/WHC544yjiP
2/5

[Yang Chen @yangchen4379]

Hi, I'm Yang! I’m a first generation Chinese-American biomedical researcher at the NIH. Check out my github pages website here! 🦠🧬💻👉 https://t.co/bEWiEuBGHj

[Karl Rohe @karlrohe]

to do good research, you must first be confused

[Ralph White III, PhD @RalphWhiteIII]

Is there a show called Science Survivor? Where we take scientists from one field and plop them in a totally different field and they complete typical tasks of the field. I wanna see chemists figure out migration patterns of birds while a Physicist learns about cell culture.

[TheScienceBreaker @sciencebreaker]

Cancer tissues are often thought to be exempt from the influence of our microbiome. @multi_omics @KnightLabNews discovered cancer-specific microbial communities. This study proposes a new class of microbial-based #cancer diagnostics.
#SciComm #OpenScience

https://t.co/vG9P0Ru9WO

[Jon-Stephen Stansel @jsstansel]

Put the salary in the job description.

No one should have to take time off work to find out the job they are interviewing for pays significantly less than the one they already have.

[Jamie Coleman, MD FACS @JJcolemanMD]

Picked up 5 yr old from school, wearing scrubs. 2 classmates approach.

Girl 1: Do you work in a hospital?
Me: Yep!
Girl 2: Are you a Dr?
Me: Yes, I am!
Girl 2: And a mommy?!
Girl 1 to Girl 2: She’s a mommy &amp; a doctor bc you can be more than 1 thing
Me: ❤️

#MouthsofBabes

[Sreenivas Bhattiprolu @digitalsreeni]

Neighbor: What does your son do?

My mom: I think he sells microscopes.

Neighbor: He got Ph.D., why can’t he find a stable job?

My mom: I am tired of telling him.

(What I actually do: Work at Zeiss and help researchers with image analysis)