My annual reminder; if you propose doing large scale data gathering and analysis, just a *one sentence* power calculation, or "we have confidence this approach can provide robust results due to similar work of XXX in system YYY with similar sample sizes".
Why is this important in a grant? As a reviewer wont be able to fully check your power calculation (usually) but I do want to see that you are honest with *yourself* about whether the stats are going to work out. Too few samples, expected weak effects => it's never going to work
If your power calculation (which will always be pulling numbers out of the air for effect size etc; such is science) says its very unlikely you will find a credible result then... you need to reset your goals.
For me, a "technology pilot" which is framed about getting the data generation to the next level and explore sources of variance *is absolutely fine* and I prefer this to an unrealistic "and then we will associated with xx disease samples"
I appreciate some reviewers want to see the xx disease samples (not just normals, or cell lines), in which case I think the best way is to say ...
"we will also run a substantial number of disease samples to ensure the applicability of the technology to these samples, assessing variance from these samples, and we will have a reasonable chance of detecting large effects present in the disease/normal contrast".

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Ewan Birney

Ewan Birney Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @ewanbirney

10 Sep
As we enter yet another period of COVID uncertainity over outcomes (due mainly to human behaviour - what does "baseline/new normal" contacts look like in an European Autumn/Winter) a reminder about models. There are at least 3 different types; explanatory, forecast and scenario.
Explanatory - usually retrospective data to fit an understanding of the world (say infection->hospitalistion/not->death/discharge) for time series. Examples: excess deaths attributable to COVID, vaccine efficacy models and biological properties of variants.
Forecast - fit an up to date time series to understand outcomes in the near future, sometimes just to understand "now" (hence "nowcasting"). Examples: R rate and near time extrapolation; hospitalisation capacity near term management (often not public).
Read 8 tweets
5 Sep
COVID thoughts from London, after a yesterday's day of slow cricket; TL;DR - the pandemic is reasonably predictable except for human behaviour on contacts; Europe will be likely navigating a complex winter; US (still) needs to vaccinate; The world needs more vaccines.
Context: I am an expert in genetics and computational biology. I know experts in viral genomics, infectious epidemiology, immunology and clinical trials. I have some COIs - I am a longestablished consultant to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory human virus where a subset of people infected get a horrible disease, COVID, often leading to death. Left unchecked many people would die and healthcare systems would have overflowed.
Read 25 tweets
29 Aug
COVID thoughts from London as back to school and work looms for England. TL;DR Vaccines work; Delta is our hardest test; the real question is how fast can we vaccinate the planet but many developed countries are running serious, largely avoidable, risks now and coming months
Context: I am genetics and computational biology expert. I know experts in viral genomics, infectious disease epidemiology, clinical trials and immunology. I have some COIs: I am a long standing consultat to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory virus, distributed by both droplets and floating aerosols, which sometimes causes a delibating disease, COVID, mainly in older and overweight people. If left unchecked, many people would die and many more suffer long term health issues.
Read 27 tweets
8 Aug
Dear journalists / editors covering COVID / this delta wave. Some of you are ... great (genuinely) - its not easy out there crafting a path thru information, speculation+ crankiness. But others... time to up your game. Here are some rookie mistakes in describing what is going on:
1. Please please stop with the % vaccinated in hospital. This is genuinely a meaningless statistic. It is just bonkers wrong to quote it. Trivially if a population is 100% vaccinated then 100% of the people in that population's hospital will be vaccinated.
What you want is something surprisingly tricky to calculate; the counterfactual of how many people should be in hospital if no vaccine. Thankfully there is an easy way of doing this which is referring back to the Alpha wave (wave 2/3 depending on counting system in each country)
Read 17 tweets
5 Aug
Had another moment of "well, yes, but people *are* different" and "you geneticists use continental groups in your analysis" as we skirted around discussions of ethnicity / race in health impacts. TL;DR Partially correct but the underlying mindset that ethnicity=genetics is wrong
Let's deal with the correct things first. Yes, people are different partly (sometimes mainly) due to genetics. Visibly, eg height, weight, hair colour, skin colour, smoking habits + invisibly, eg cholesterol levels, heart trabeculation levels, likelihood of getting breast cancer
Some of these visible differences we integrate into the gestalt assessment of ourselves and others for ethnicity, as represented by self identified ethnicity boxes which people tick, eg "Black British, White English, British Indian, British xxx", gloriously variable by society
Read 26 tweets
4 Aug
Ah. I love the smell of freshly baked data/analysis, well controlled false discovery rate (QQ plot) and just ... so many results. Which of the thousands of beautiful stars in the sky does one pull out to discuss? Biology is so endless and wonderful in its detail...
... to alter (butcher?) a passage from a far far wiser and more thoughtful man than me....
It is interesting to contemplate a tangled set of genetic results, associated to both well known genes and entirely anonymous regions of the genome, stories from physiology of old and hints of new insights, and to reflect ...
Read 5 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

:(