Best Genomics Data Analysis Software for Python

Compare the Top Genomics Data Analysis Software that integrates with Python as of July 2025

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This a list of Genomics Data Analysis software that integrates with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.

What is Genomics Data Analysis Software for Python?

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 Genomics Data Analysis software for Python currently available using the table below. This list is updated regularly.

1

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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2

Microsoft Genomics

Microsoft

Instead of managing your own data centers, take advantage of Microsoft's scale and experience in running exabyte-scale workloads. Because Microsoft Genomics is on Azure, you have the performance and scalability of a world-class supercomputing center, on demand in the cloud. Take advantage of a backend network with MPI latency under three microseconds and non-blocking 32 gigabits per second (Gbps) throughput. This backend network includes remote direct memory access technology that enables parallel applications to scale to thousands of cores. Azure provides you with high memory and HPC-class CPUs to help you get results fast. Scale up and down based on what you need and pay only for what you use to reduce costs. Tackle data sovereignty requirements with a worldwide network of Azure data centers and adhere to your compliance requirements. Easily integrate into your existing pipeline code using a REST-based API and simple Python client.

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3

XetaBase

Zetta Genomics

The unique XetaBase platform simplifies tertiary analysis, aggregating, indexing, and enriching secondary genomic data, enabling continual re-interpretation to unlock research and clinical insight. XetaBase accelerates data management and the cost-effective application of genomic data in the lab and clinic. XetaBase encompasses genomic scale, the greater the volume and complexity, the greater the insight and outcomes. XetaBase is a genomic-native technology, built on the open-source, OpenCB software platform to meet the scale, speed, and re-interpretation demands of genomic medicine. Zetta Genomics delivers genomic data management fit for the precision medicine age. XetaBase is a completely novel solution to the challenges of genomic data. It sweeps away obsolete flat file approaches to bring meaningful and actionable genomic data into the lab and the clinic. XetaBase empowers continual re-interpretation while scaling seamlessly as databases grow to encompass genome sequences.

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4

CZ CELLxGENE Discover

CZ CELLxGENE

Select two custom cell groups based on metadata to find their top differentially expressed genes. Leverage millions of cells from the integrated CZ CELLxGENE corpus for powerful analysis. Execute interactive analyses on a dataset to explore how patterns of gene expression are determined by spatial, environmental, and genetic factors using an interactive speed no-code UI. Understand published datasets or use them as a launchpad to identify new cell sub-types and states. Census provides access to any custom slice of standardized cell data available on CZ CELLxGENE Discover in R and Python. Explore an interactive encyclopedia of 700+ cell types that provides detailed definitions, marker genes, lineage, and relevant datasets in one place. Browse and download hundreds of standardized data collections and 1,000+ datasets characterizing the functionality of healthy mouse and human tissues.

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