Tagged statistics

Design Bayesian clinical trials with dose-finding, priors and platform designs

Run logistic regression for trial outcomes with marginal effects and Firth fits

Write clinical trial statistical reports with Table 1, analysis sets and estimands

Detect introgression between populations with D-statistics and TreeMix

Build Manhattan, QQ and LocusZoom plots from GWAS summary statistics

Add p-value brackets and significance asterisks to distribution plots

Compare cell-type composition across IMC cohorts with patient-level statistics

Annotate lipids at honest confidence levels and run lipid-aware statistics

Run metabolomics statistics with scaling choices, PLS-DA and permutation checks

Turn metagenome profiler tables into honest figures and diversity statistics

Run Bayesian phylogenetics with MrBayes and BEAST2 and check convergence

Infer population structure with PCA, ADMIXTURE and FST statistics

Analyze population genetics in Python with scikit-allel diversity and FST statistics

Scan genomes for selection with SFS tests, iHS, XP-EHH and FST statistics

Calculate N50, auN, GC content and length statistics for sequence sets

Detect spatially variable genes and cell colocalization with Squidpy

Compute VCF quality metrics like Ti/Tv, missingness and HWE with bcftools stats

Write MATLAB performance tests with matlab.perftest and statistical timing

Analyze experiment results with statistics, comparison tables and written insights

Analyze experiment results with statistics and draft the results section of a paper

Write structured peer reviews with checklists for methods, statistics and reporting

Fetch cis-eQTL statistics for a gene region from the EBI eQTL Catalogue

Fetch GWAS summary statistics for one genomic window from the GWAS Catalog

Harmonize GWAS summary statistics from common tools into one canonical table

Fetch regional plasma pQTL summary statistics from UK Biobank proteomics data

Verify quotes, statistics and citations against live primary sources with an audit log

Analyze CSV files with Python and pandas to compute statistics and insights

Build hierarchical Bayesian cognitive models in Stan or PyMC with diagnostics

Choose mixed models, multiple-comparison corrections and Bayesian methods for cognitive data

Analyze event-related potentials from preprocessing through statistical testing

Share anonymized statistics on which skills get used most with the community

Plan and set up A/B tests with hypotheses, variants and statistical checks

Run Python for statistics, numerical computation and simulations to verify results

Clean a dataset, run exploratory analysis and statistical tests, then report results

Run hypothesis tests, correlation analysis and multiple testing corrections

Run GIS operations, spatial statistics and satellite image processing

Tokenize text, tag parts of speech and run corpus statistics with NLTK

Review manuscripts for methods, statistics and clarity with constructive feedback

Run hypothesis tests, optimization and signal processing with SciPy

Run Bayesian analysis, survival curves, time series and power analysis

Run regressions, hypothesis tests and time series analysis with statsmodels