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Multi-dimensional Annotation Class Integrative Estimation

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MACIE (Multi-dimensional Annotation Class Integrative Estimation)

Description

Thank you for your interest in MACIE. MACIE (Multi-dimensional Annotation Class Integrative Estimation) is an unsupervised multivariate mixed model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and noncoding variants in the human genome.

Data Availability and Reproducibility

The MACIE scores (and other integrative scores) used in all benchmarking examples are available for download here. Precomputed MACIE scores for all nonsynonymous coding, synonymous coding and noncoding variants in the human genome is under construction.

All genomic coordinates are given in NCBI Build 37/UCSC hg19.

Reference

Xihao Li*, Godwin Yung*, Hufeng Zhou, Ryan Sun, Zilin Li, Yaowu Liu, Iuliana Ionita-Laza, Xihong Lin (2021+) "A Multi-dimensional Integrative Scoring Framework for Predicting Functional Variants in the Human Genome".

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