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#k12 #VO #PO #OP #OOP #Educatie & #Education **DUTCH** "de" plek voor ieder die Onderwijs een warm hart toedraagt. **English** "the" place for everyone who work for and with Education.

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#statistics

71 posts44 participants4 posts today
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Ed Summers

Did I do something dumb with #statistics here? (please be gentle)

I have a list of 4,496,871 Census FTP URLs (thx @andrewjbtw ). I randomly sampled 385 of them, and looked them up in the Wayback Machine. 178 of them have one or more archival snapshots that were 200 OK.

So, based on this sample, I can say with 95% confidence, and a 5% margin of error, that only 46% of these Census FTP URLs have a snapshot in the Wayback Machine.

I hope I did something wrong because this sounds not great?

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fediverseobserver

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fediverseobserver

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fediverseobserver

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fediverseobserver

Found 5 new servers and 12 servers died off since 5 hours ago

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fediverseobserver

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fediverseobserver

Found 44 new servers and 30 servers died off since 9 hours ago

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fediverseobserver

Found 5 new servers and 12 servers died off since 5 hours ago

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fediverseobserver

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Ralph Crützen

Wie heeft ervaring met de programmeertaal R?

Ik ben aan het uitzoeken of dit bij 4 havo/vwo wiskunde A als praktische opdracht gebruikt kan worden. Nu doen we iets met Excel, maar daar wil ik van af.

Ik wil zelf lesmateriaal gaan schrijven, maar moet eerst weten of het geschikt is voor dit niveau.

#math#programming#coding
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Phil Greer

I have worked on a lot of papers, this is my first preprint.

Analyzing large biobanks of genomic data requires a fresh look at our quality control metrics, especially as we move to NGS and more diverse populations.

You may be throwing out biologically important variants.

I would be happy to hear feedback.

#UKBiobank #HardyWeinbergEquilibrum
#statistics #statisticalgenetics #GWAS #genetics #preprint

medrxiv.org/content/10.1101/20

medRxiv · A reassessment of Hardy-Weinberg equilibrium filtering in large sample Genomic studiesHardy Weinberg Equilibrium (HWE) is a fundamental principle of population genetics. Adherence to HWE, using a p-value filter, is used as a quality control measure to remove potential genotyping errors prior to certain analyses. Larger sample sizes increase power to differentiate smaller effect sizes, but will also affect methods of quality control. Here, we test the effects of current methods of HWE QC filtering on varying sample sizes up to 486,178 subjects for imputed and Whole Exome Sequencing (WES) genotypes using data from the UK Biobank and propose potential alternative filtering methods. METHODS Simulations were performed on imputed genotype data using chromosome 1. WES GWAS (Genome Wide Association Study) was performed using PLINK2. RESULTS Our simulations on the imputed data from Chromosome 1 show a progressive increase in the number of SNPs eliminated from analysis as sample sizes increase. As the HWE p-value filter remains constant at p<1e-15, the number of SNPs removed increases from 1.66% at n=10,000 to 18.86% at n=486,178 in a multi-ancestry cohort and from 0.002% at n=10,000 to 0.334% at n=300,000 in a European ancestry cohort. Greater reductions are shown in WES analysis with a 11.91% reduction in analyzed SNPs in a European ancestry cohort n=362,192, and a 32.70% reduction in SNPs in a multi-ancestry dataset n=463,605. Using a sample size specific HWE p-value cutoff removes ∼2.25% of SNPs in the all ancestry cohort across all sample sizes, but does not currently scale beyond 300,000 samples. A hard cutoff of +/- 20% deviation from HWE produces the most consistent results and scales across all sample sizes but requires additional user steps. CONCLUSION Testing for deviance from HWE may still be an important quality control step in GWAS studies, however we demonstrate here that using an HWE p-value threshold that is acceptable for smaller sample sizes will be inappropriate for large sample studies due to an unnecessarily high number of variants removed prior to analysis. Rather than exclude variants that fail HWE prior to analysis it may be better to include all variants in the analysis and examine their deviation from HWE afterward. We believe that adjusting the cutoffs will be even more important for large whole genome sequencing results and more diverse population studies. KEY TAKEAWAYS ### Competing Interest Statement BB and AS are full time employees of DNAnexus, Inc. PG and DW are full time employees of Ariel Precision Medicine Inc ### Funding Statement Authors were compensated for time contributed to the study by their respective institutions. Their respective institutions also paid for any compute needed to complete experiments on the UKBRAP. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available in supplementary material. * HWE : Hardy Weinberg Equilibrium GWAS : Genome Wide Association Study WES : Whole Exome Sequencing WGS : Whole Genome Sequencing MAF : Minor Allele Frequency SNP QC : quality control EO : European Only GSD : Gallstone Disease UKB : UK Biobank UKB RAP : UK Biobank Research Analysis Platform MHC : Major Histocompatibility Complex
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Ergative Absolutive

Ok, just migrated to wandering.shop. Reposting #Introduction here, because I can. In the spirit of poking first-post paralysis in the eye and chucking things out in the void, here are some hashtags. I hope the void will chuck something interesting back out.

Hobbies: #sciencefiction #fantasy #figureskating #calligraphy #baking #islamicgeometricart (hah! New hashtag! O brave new world, that hath such hashtags yet unclaimed in it)

Work: #linguistics #psycholinguistics #academia #statistics #ucu

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naught101

Just realising I've never done an #introduction ..

living in #moolabinba/#newcastle, #australia, #earth, on the Orion-Cygnus Arm of the Milky Way, somewhere in the Laniakea Supercluster.

I do questionable things with numbers, in particular related to #climate #science, #statistics, and #risk.

I also turn numbers into #music via #musicproduction and #synthesis, and playing #drums.

I'm interested in using these things for #socialchange. Keeping a close eye on #auspol.

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Dr. Robert M Flight

I guess it might be time for an #introduction on this site.

I am a research analyst in academic #bioinformatics. I'm interested in new computational #metabolomics methods, #transcriptomics, data integration, etc.

I know just enough #statistics to be useful / dangerous, depending on your POV.

I use #rstats heavily (in a lab that mostly uses #python), and believe in the value of graphing your data, as well as making work reproducible and as open as possible.

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