Best Free Genomics Data Analysis Software

Compare the Top Free Genomics Data Analysis Software as of April 2025

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What is Free Genomics Data Analysis Software?

Genomics data analysis software helps researchers and scientists analyze and interpret large-scale genomic data, enabling insights into genetic variations, mutations, and biological functions. It provides tools for processing raw genomic sequences, aligning them to reference genomes, and identifying significant patterns or mutations. The software often includes features like data visualization, statistical analysis, and integration with other biological datasets to support comprehensive research. By automating complex analyses, genomics data analysis software accelerates research workflows and improves the accuracy of genetic insights. Ultimately, it advances scientific discovery and personalized medicine by enabling a deeper understanding of the human genome and other organisms. Compare and read user reviews of the best Free Genomics Data Analysis software currently available using the table below. This list is updated regularly.

1

JADBio AutoML

JADBio

JADBio is a state-of-the-art automated Machine Learning Platform without the need for coding. With its breakthrough algorithms it can solve open problems in machine learning. Anybody can use it and perform a sophisticated and correct machine learning analysis even if they do not know any math, statistics, or coding. It is purpose-built for life science data and particularly molecular data. This means that it can deal with the idiosyncrasies of molecular data such as very low sample size and very high number of measured quantities that could reach to millions. Life scientists need it to understand what are the features and biomarkers that are predictive and important, what is their role, and get intuition about the molecular mechanisms involved. Knowledge discovery is often more important than a predictive model. So, JADBio focuses on feature selection and its interpretation.

Starting Price: Free

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2

Genome Analysis Toolkit (GATK)

Broad Institute

Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size. The GATK is the industry standard for identifying SNPs and indels in germline DNA and RNAseq data. Its scope is now expanding to include somatic short variant calling and to tackle copy number (CNV) and structural variation (SV). In addition to the variant callers themselves, the GATK also includes many utilities to perform related tasks such as processing and quality control of high-throughput sequencing data and bundles the popular Picard toolkit. These tools were primarily designed to process exomes and whole genomes generated with Illumina sequencing technology, but they can be adapted to handle a variety of other technologies and experimental designs.

Starting Price: Free

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3

Galaxy

Galaxy

Galaxy is an open source, web-based platform for data-intensive biomedical research. If you are new to Galaxy start here or consult our help resources. You can install your own Galaxy by following the tutorial and choosing from thousands of tools from the tool shed. This instance of Galaxy is utilizing infrastructure generously provided by the Texas Advanced Computing Center. Additional resources are provided primarily on the Jetstream2 cloud via ACCESS, and with support from the National Science Foundation. Quantify, visualize, and summarize mismatches in deep sequencing data. Build maximum-likelihood phylogenetic trees. Phylogenomic/evolutionary tree construction from multiple sequences. Merge matching reads into clusters with TN-93. Remove sequences from a reference that are within a given distance of a cluster. Perform maximum-likelihood estimation of gene essentiality scores.

Starting Price: Free

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4

BioTuring Browser

BioTuring Browser

Explore hundreds of curated single-cell transcriptome datasets, along with your own data, through interactive visualizations and analytics. The software also supports multimodal omics, CITE-seq, TCR-seq, and spatial transcriptomic. Interactively explore the world's largest single-cell expression database. Access and query insights from a single-cell database of millions of cells, fully annotated with cell type labels and experimental metadata. Not just creating a gateway to published works, BioTuring Browser is an end-to-end solution for your own single-cell data. Import your fastq files, count matrices, Seurat, or Scanpy objects, and reveal the biological stories inside them. Get a rich package of visualizations and analyses in an intuitive interface, making insight mining from any curated or in-house single-cell dataset become such a breeze. Import single-cell CRISPR screening or Perturb-seq data, and query guide RNA sequences.

Starting Price: Free

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5

ESMFold

Meta

ESMFold shows how AI can give us new tools to understand the natural world, much like the microscope, which enabled us to see into the world at an infinitesimal scale and opened up a whole new understanding of life. AI can help us understand the immense scope of natural diversity, and see biology in a new way. Much of AI research has focused on helping computers understand the world in a way similar to how humans do. The language of proteins is one that is beyond human comprehension and has eluded even the most powerful computational tools. AI has the potential to open up this language to our understanding. Studying AI in new domains such as biology can also give insight into artificial intelligence more broadly. Our work reveals connections across domains: large language models that are behind advances in machine translation, natural language understanding, speech recognition, and image generation are also able to learn deep information about biology.

Starting Price: Free

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6

Cellenics

Biomage

Turn your single-cell RNA sequencing data into meaningful insight with Cellenics software. Biomage hosts a community instance of Cellenics, an open source analytics tool for single-cell RNA sequencing data that has been developed at Harvard Medical School. It enables biologists to explore single-cell datasets without writing code and helps scientists and bioinformaticians to work together more effectively. It takes you from count matrices to publication-ready figures in just a few hours and can be integrated seamlessly with your workflow. It’s fast, interactive, and user-friendly. And it’s cloud-based, secure, and scaleable. The Biomage-hosted community instance of Cellenics is free for academic researchers with small/medium-sized datasets (up to 500,000 cells). It’s used by 3000+ academic researchers studying cancer, cardiovascular health, and developmental biology.

Starting Price: Free

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