.png){kind=icon}
返回
Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation
.png){kind=icon}
PRE
AI
DOI：10.1109/TCBB.2017.2708701.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
High-throughput sequencing techniques have generated massive quantities of genotype data. Haplotype phasing has proven to be a useful and effective method for analyzing these data. However, the quality of phasing is undermined due to missing information. Imputation provides an effective means of improving the underlying genotype information. For model organisms, imputation can rely on an available reference genotype panel and a physical or genetic map. For non-model organisms, which often do not have a genotype panel, it is important to design an imputation technique that does not rely on reference data. Here, we present Accurate Data-Driven Imputation Technique (ADDIT), which is composed of two data-driven algorithms capable of handling data generated from model and non-model organisms. The non-model variant of ADDIT (referred to as ADDIT-NM) employs statistical inference methods to impute missing genotypes, whereas the model variant (referred to as ADDIT-M) leverages a supervised learning-based approach for imputation. We demonstrate that both variants of ADDIT are more accurate, faster, and require less memory than leading state-of-the-art imputation tools using model (human) and non-model (maize, apple, and grape) genotype data.
Keyword:
Genotype imputation
single nucleotide polymorphisms (SNPs)
next-generation and high-throughput sequencing
machine learning
big data
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
3.4
论文数:
3.3K
被引数:
6.4K
机构
引用论文
Productivity enhancement of solar still by PCM and Nanoparticles miscellaneous basin absorbing materials.png)
Desalination
OAAI
DesalinationIF0
OAAI分享收藏The genome of the domesticated apple (Malus x domestica Borkh.)驯化苹果 (Malus x domestica bokh.) 的基因组NATURE GENETICSOAAI
NATURE GENETICSIF31.8
OAAI分享收藏A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association StudiesPLOS GENETICSOAAI
PLOS GENETICSIF3.7
OAAI分享收藏
查看更多内容