miniABS (mini Absolute Breast Cancer Subtyper) is an absolute, single-sample subtype classifier for breast cancer using Random Forest model of pairwise gene expression ratios (PGER) among 11 functional genes. With a systematic gene selection and reduction step, we aimed to minimize the size of gene set without losing a functional interpretability of the classifier. We validated the model performance using a large, heterogeneous cohort that consists of multiple public datasets across four different platforms. We anticipate that the high accuracy and reproducibility of miniABS may provide a SSP at a low cost, as well as providing a platform for cross comparison among gene expression datasets generated with different technical platforms.

Features

  • an absolute, single-sample subtype classifier of breast cancer with 11 functional genes

Project Activity

See All Activity >

Follow miniABS

miniABS Web Site

Other Useful Business Software
Enterprise-grade ITSM, for every business Icon
Enterprise-grade ITSM, for every business

Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
Try it Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of miniABS!

Additional Project Details

Registered

2018-05-15