Northstar Bio builds software that turns sequencing data into biology. Single-cell RNA-seq, bulk RNA-seq, and immune profiling, analyzed end to end in one platform. Sequencing has never been cheaper to run, or harder to interpret. A dataset that takes days to generate can take months to understand, if a bioinformatician is available at all. We exist to close that gap.
No code. No command line. No queue behind a bioinformatics core. Drag in FASTQ files, count matrices, Seurat objects, or H5AD and work through the analysis in plain language: quality control and doublet detection, clustering and integration, differential expression, pathway and network analysis, trajectories, and immune repertoire profiling. Single-cell, bulk RNA-seq, and immune profiling run in one workflow instead of three toolchains stitched together. For wet-lab scientists, guided mode carries the pipeline end to end. For bioinformaticians and experienced users, manual mode exposes every threshold and parameter with the reasoning behind each default written out, so you can override what you disagree with and keep what you don't. Results stay interactive: UMAP, tSNE, heatmap, and volcano views update in real time, and you can drill into any gene, marker, or pathway and run further analysis on what you are looking at. In a controlled study of 51 participants, our conversational approach reached 90% accuracy against 28% for standard statistical software, 27% faster and with 61% fewer interactions.
Every result traces back to the evidence that produced it. Our annotation engine scores curated marker signatures against your data rather than matching your cells to a black box trained on someone else's atlas, and it does not stop at a one-word label. A cluster comes back with its full biological address and its trajectory, each axis carrying the marker genes that drove the call and a confidence tier:
Where the evidence is too thin, an axis comes back as "not called" rather than a confidently wrong guess. The same principle governs the statistics. Tests are selected automatically from your data type, distribution, and study design, so you do not need to know which test applies or why. The logic behind every selection is written out in plain language, along with multiple-testing correction and effect sizes reported by default. Nothing is a black box. What you get is a defensible methods trail, one that survives peer review, an audit, and your own re-analysis a year later.
Your data never leaves your machine. No cloud upload, no third-party storage, no account standing between you and your own counts matrix. The platform installs on hardware you already have, a laptop, a lab workstation, or your institution's server, and runs with no internet connection after setup, reaching outward only when you explicitly ask it to search a public repository. For clinical, regulated, and IP-sensitive research, that is not a preference but a requirement: hospitals handling protected patient data and companies protecting unpublished targets cannot ship samples to a cloud API, which is precisely why so much of the current generation of tools remains closed to them.
We were founded by researchers who lived it: years at the bench waiting on analyses, context lost in handoffs between biologist and analyst, results that couldn't be reproduced a year later. The bottleneck was never the biology. It was the tooling.
So we built our own. Northstar Bio develops bioinformatics software that puts analysis back in the hands of the scientist who designed the experiment, from raw sequencing data to publication-ready biology, without writing a line of code.
Northstar Bio is a Massachusetts-based company built by a team spanning immuno-oncology, machine learning, and systems engineering. We're building for the researchers who've been waiting.
Request a demo and we will walk you through the platform with a dataset of your choosing.
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