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Предыдущая публикация
Noam Teyssier

Currently the only tool that supports this data type is CellRanger and we show that cyto provides runtimes an order of magnitude faster (16x), uses less than half the memory, dramatically reduces CPU-hours (30x) and reduces total IO by more than 5x.

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Noam Teyssier

cyto was built from the ground up to be modular and to expose the individual modules to the user. Each step is highly optimized and can be run independently, perfect for production scale workflows as it allows for better parallelization and resource allocation on smaller nodes

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1 прямых ответов · 4 сообщений

Noam Teyssier

We also show that we can reproduce the results of CellRanger at a fraction of the resource cost. Our concordance is above 99.85% as measured via Spearman on matched cell UMIs and our lower-dimensional representations show perfect overlap with no method specific clustering.

Ответ для Noam Teyssier
Noam Teyssier

cyto is the first large-scale bioinformatics project to build with BINSEQ. Switching to BINSEQ can achieve mapping rates of 50M reads per second reduce your storage requirements by about 40%. github.com/ArcInstitute...

GitHub - ArcInstitute/binseq: A high efficiency binary format for sequencing dataA high efficiency binary format for sequencing data - ArcInstitute/binseqgithub.com
Ответ для Noam Teyssier
Noam Teyssier

cyto is free, open-source, and production-ready. Built in Rust for reliability at scale. Currently supports 10x Flex GEX and CRISPR, with more modalities coming. Try it out and let us know how it works for you! github.com/ArcInstitute...

GitHub - ArcInstitute/cyto: A mapper for single cell sequencing reads with abstract geometriesA mapper for single cell sequencing reads with abstract geometries - ArcInstitute/cytogithub.com
Ответ для Noam Teyssier
Nhi Nguyen

50M reads/sec with 40% storage reduction is impressive! Storage and I/O bottlenecks are real pain points for large-scale sequencing projects. Great to see Arc Institute tackling this.