pandas

Use when working with NumPy, ndarray-based numerical computing, array creation, vectorization, broadcasting, linear algebra, random sampling, or scientific file I/O in Python. NumPy provides the n-dim

2 shared topics • 1 shared operation

ggplot2 — grammar of graphics implementation in R for creating complex, layered statistical visualizations. Supports scatter plots, bar charts, histograms, boxplots, heatmaps, faceted plots, and custo

2 shared topics

Pychopper — Nanopore direct cDNA read preprocessing tool that identifies, orients, and trims full-length reads using primer detection (pHMM or alignment). Rescues fused reads by dynamic programming, e

2 shared topics

RTG Tools — Java-based toolkit from Real Time Genomics for haplotype-aware variant call comparison, VCF filtering, statistics, and pedigree analysis. Primary use: vcfeval for benchmarking variant call

2 shared topics

Seaborn — statistical data visualization library built on matplotlib. Provides high-level functions for relational plots (scatterplot, lineplot), distribution plots (histplot, kdeplot, ecdfplot), cate

2 shared topics