Sequencing Machines

Seqcolyte is an open-source, protocol-aware platform for sequencing quality control and root-cause diagnosis. I built a workflow in which Claude Code agents convert protocols and laboratory context into structured, validated assay specifications—including oligos, barcode and UMI layouts, and expected molecules — then compare raw FASTQ or BAM data against those expectations using deterministic QC tools. When an initial report flags any issue, the agent can propose a falsifiable hypothesis, write and run a targeted diagnostic script, and feed the resulting metrics back into an evidence-backed report. The project was motivated by single-cell experiment runs where a standard report flags a symptom, such as recovering about 2,000 cells instead of 45,000, but leaves several competing explanations. I found that grounding the analysis in the protocol makes it possible to connect abnormal read/cell signatures to specific library-preparation steps, candidate root causes, confirmatory tests, and recovery actions. The current prototype supports Illumina and Oxford Nanopore single-cell workflows, with reproducible simulations and labeled failures for evaluation. This matters because failed sequencing runs cost precious samples, time, and money. Seqcolyte helps bench scientists, sequencing cores, and computational teams move from a generic QC alert to a testable, reproducible diagnosis and a concrete next action for experiment and technology optimization. Next, I’m expanding assay and platform coverage and benchmarking Seqcolyte on more real failures. The goal is to move from a QC alert to an evidence-backed, reproducible and accurate diagnosis.

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