Best Bioinformatics Software for Linux

Ruffus is a computation pipeline library for python. It is open-sourced, powerful and user-friendly, and widely used in science and bioinformatics. Ruffus is designed to allow scientific and other analyses to be automated with the minimum of fuss and the least effort. Suitable for the simplest of tasks. Handles even fiendishly complicated pipelines which would cause make or scons to go cross-eyed and recursive. No "clever magic", no pre-processing. Unambitious, the lightweight syntax which tries to do this one small thing well. Ruffus is available under the permissive MIT free software license. This permits free use and inclusion even within proprietary software. It is good practice to run your pipeline in a temporary, “working” directory away from your original data. Ruffus is a lightweight python module for building computational pipelines. Ruffus requires Python 2.6 or higher or Python 3.0 or higher.

Geneious Prime makes bioinformatics accessible by transforming raw data into visualizations that make sequence analysis intuitive and user-friendly. Simple sequence assembly and easy editing of contigs. Automatic annotation for gene prediction, motifs, translation, and variant calling. Genotype microsatellite traces with automated ladder fitting and peak calling and generates tables of alleles. Beautiful visualizations of annotated genomes and assemblies are displayed in a highly customizable sequence view. Powerful SNP variants analysis, simple RNA-Seq expression analysis, and amplicon metagenomics. Design and test PCR and sequencing primers and create your own searchable primer database. Geneious Biologics is a flexible, scalable, and secure way to streamline your antibody analysis workflows, create high-quality libraries and select the optimal therapeutic candidates.

OmicsBox is a leading bioinformatics solution that offers end-to-end data analysis of genomes, transcriptomes, metagenomes, and genetic variation studies. The application is used by top private and public research institutions worldwide and allows researchers to easily process large and complex data sets, and streamline their analysis process. It is designed to be user-friendly, efficient, and with a powerful set of tools to extract biological insights from omics data. The software is structured in different modules, each with a specific set of tools and functions designed to perform different types of analysis, such as de-novo genome assemblies, genetic variation analysis, differential expression analysis, and taxonomic classifications of microbiome data, including the functional interpretation and rich visualizations of results. The functional analysis module includes the popular Blast2GO annotation methodology and makes OmicsBox particularly suited for non-model organism research

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.

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.

This free tool delivers stunning visualizations of your genomic data that give you the power to see what is occurring at each base pair in your samples. GenomeBrowse runs as a native desktop application on your computer. No longer do you have to sacrifice speed and interface quality to obtain a consistent cross-platform experience. It was developed with performance in mind to deliver a faster and more fluid browsing experience than any other genome browser available. GenomeBrowse is also integrated into the powerful Golden Helix VarSeq variant annotation and interpretation platform. If you love the visualization experience of GenomeBrowse, check out VarSeq for filtering, annotating, and analyzing your data before utilizing the same visualization interface. GB can display all your alignment data. Looking at all your samples in one view can help you spot contextually relevant findings.

MEGA (Molecular Evolutionary Genetics Analysis) is a powerful and user-friendly software suite designed for analyzing DNA and protein sequence data from species and populations. It facilitates both automatic and manual sequence alignment, phylogenetic tree inference, and evolutionary hypothesis testing. MEGA supports a variety of statistical methods including maximum likelihood, Bayesian inference, and ordinary least squares, making it an essential tool for comparative sequence analysis and understanding molecular evolution. MEGA offers advanced features such as real-time caption generation to help explain the results and methods used in analysis and the maximum composite likelihood method for estimating evolutionary distances. The software is equipped with robust visual tools like the alignment/trace editor and tree explorer and supports multi-threading for efficient processing. MEGA can be run on multiple operating systems, including Windows, Linux, and macOS.

Cufflinks assemble transcripts, estimate their abundances and test for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one, taking into account biases in library preparation protocols. Cufflinks was originally developed as part of a collaborative effort between the Laboratory for Mathematical and Computational Biology. In order to make it easy to install Cufflinks, we provide a few binary packages to save users from the occasionally frustrating process of building Cufflinks, which requires that you install the libraries. Cufflinks includes a number of tools for analyzing RNA-Seq experiments. Some of these tools can be run on their own, while others are pieces of a larger workflow.

The Bioconductor project aims to develop and share open source software for precise and repeatable analysis of biological data. We foster an inclusive and collaborative community of developers and data scientists. Resources to maximize the potential of Bioconductor. From basic functionalities to advanced features, our tutorials, guides, and documentation have you covered. Bioconductor uses the R statistical programming language and is open source and open development. It has two releases each year and an active user community. Bioconductor provides Docker images for every release and provides support for Bioconductor use in AnVIL. Founded in 2001, Bioconductor is an open-source software project widely used in bioinformatics and biomedical research. It hosts over 2,000 R packages contributed by over 1,000 developers, with over 40 million downloads per year. Bioconductor has been cited in more than 60,000 scientific publications.

With its comprehensive suite of integrated software, StarDrop™ delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop™ enables a seamless flow from the latest data through predictive modeling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the discovery process. Successful compounds require a balance of many different properties. StarDrop™ guides you through this multi-parameter optimization challenge to target compounds with the best chance of success, saving you time and resources by enabling you to synthesize and test fewer compounds.

Swiss-PdbViewer (aka DeepView) is an application that provides a user-friendly interface allowing to analysis of several proteins at the same time. The proteins can be superimposed in order to deduce structural alignments and compare their active sites or any other relevant parts. Amino acid mutations, H-bonds, angles, and distances between atoms are easy to obtain thanks to the intuitive graphic and menu interface. Swiss-PdbViewer (aka DeepView) has been developed since 1994 by Nicolas Guex. Swiss-PdbViewer was initially tightly linked to SWISS-MODEL, an automated homology modeling server developed within the Swiss Institute of Bioinformatics (SIB) at the Structural Bioinformatics Group at the Biozentrum in Basel. However, the SWISS-MODEL web interface evolved to a point where it is now possible to use it directly for advanced modeling. Maintaining a direct interface with Swiss-PdbViewer is too complex and no longer supported.

Loupe Browser is a powerful visualization software that provides the intuitive functionality you need to explore and analyze your 10x Genomics Chromium and Visium data. You can also convert your Seurat objects into Loupe Browser files using the LoupeR package. The navigation and interactive functionality of the Loupe Browser interface uses a lung squamous cell carcinoma dataset. The workspace is centered around the view panel in which single points representing cell barcodes are shown in a variety of projections. Each point represents a single barcode, the vast majority of which correspond to a single cell. The default projection is the t-SNE plot created by the cell ranger pipeline, though other projections are available. You can drag the mouse over the cells to reposition the plot and use the mouse wheel or trackpad to zoom in and out. Cluster labels appear as you move your mouse over the plot, which is useful for data that has a high number of precomputed clusters.

Avogadro is an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible high quality rendering and a powerful plugin architecture. Avogadro is a free, open-source molecular editor and visualization tool, designed for use on Mac, Windows, and Linux in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible high quality rendering and a powerful plugin architecture.

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.