outlier-detective
Detect anomalies and outliers in datasets using statistical and ML methods. Use for data cleaning, fraud detection, or quality control analysis.
data-cleaning
Data cleaning, preprocessing, and quality assurance techniques
data-journalism
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics, or building data-driven stories. Essential for reporters, newsrooms, and researchers working with quantitative information.
BAM-filtration
Performs data cleaning and removal operations. This skill takes a raw BAM and creates a new, "clean" BAM file by actively removing artifacts: mitochondrial reads, blacklisted regions, PCR duplicates, and unmapped reads. Use this skill to "clean," "filter," or "remove bad reads" from a dataset. This is a prerequisite step before peak calling. Do NOT use this skill if you only want to view statistics without modifying the file.
