Giter Site home page Giter Site logo

shasta's Introduction

Shasta long read assembler


The complete user documentation is available here.

For quick start information see here.

See Shafin et al, Nature Biotechnology 2020 for an error analysis of the Shasta assembler and more. Reads from this paper are available here. The assembly results are here.

Here is a QUAST analysis of a Shasta assembly of CHM13 and comparison with other assemblers.

Requests for help: please file GitHub issues to report problems, request help or ask questions. Please keep each issue on a single topic when possible.


The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells.

Computational methods used by the Shasta assembler include:

  • Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.

  • Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k โ‰ˆ 10).

As currently implemented, Shasta can run an assembly of a human genome at coverage around 60x in about 3 hours using a single, large machine (AWS instance type x1.32xlarge, with 128 virtual processors and 1952 GB of memory). The compute cost of such an assembly is around $20 at AWS spot market or reserved prices.

Shasta assembly quality is comparable or better than assembly quality achieved by other long read assemblers - see this paper for an extensive analysis. However, adjustments of assembly parameters are generally necessary to achieve optimal assembly results. A set of sample configuration files is provided (in the conf directory) to assist with this process.

Acknowledgments

The Shasta software uses various external software packages. See here for more information.

Reporting Security Issues

Please note: If you believe you have found a security issue, please responsibly disclose by contacting [email protected].


The complete user documentation is available here.

For quick start information see here.


Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.