# SwarmGenomics: A Unified Pipeline for Individual‐Based Whole‐Genome Analyses

## TL;DR

SwarmGenomics is a user-friendly pipeline for whole-genome analysis that simplifies genetic studies of non-model species.

## Contribution

SwarmGenomics introduces a unified, modular pipeline for individual-based genomic analyses with minimal bioinformatics expertise.

## Key findings

- SwarmGenomics integrates seven modules for various genetic analyses, including heterozygosity and population history.
- The pipeline was successfully applied to the giant panda, revealing genetic diversity and inbreeding patterns.
- SwarmGenomics helps identify transposable element activity and microbial contamination in genomic data.

## Abstract

Advances in sequencing technologies have made whole‐genome data widely accessible, enabling research in population genetics, evolutionary biology, and conservation. However, analysing whole‐genome sequencing (WGS) data remains challenging, often requiring multiple specialised tools and substantial bioinformatics expertise. We present SwarmGenomics, a modular, user‐friendly command‐line pipeline for reference‐based genome assembly and individual‐based genetic analyses. The pipeline integrates seven modules: heterozygosity estimation, runs of homozygosity detection, Pairwise Sequentially Markovian Coalescent (PSMC) analysis, unmapped reads classification, repeat analysis, mitochondrial genome assembly, and nuclear mitochondrial DNA segment (NUMT) identification. Each module can be run independently or as part of a complete workflow. We demonstrate the pipeline's utility with a case study on the giant panda (
Ailuropoda melanoleuca
), revealing insights into genetic diversity, inbreeding history, historical population size changes, transposable element activity, and microbial contamination. SwarmGenomics lowers the entry barrier for genomic analysis of diploid, non‐model species, serving both as a research and teaching tool. The pipeline and documentation are available at https://github.com/AureKylmanen/Swarmgenomics.