eXtasy: variant prioritization by genomic data fusion
نویسندگان
چکیده
منابع مشابه
Gene Prioritization by Compressive Data Fusion and Chaining
Data integration procedures combine heterogeneous data sets into predictive models, but they are limited to data explicitly related to the target object type, such as genes. Collage is a new data fusion approach to gene prioritization. It considers data sets of various association levels with the prediction task, utilizes collective matrix factorization to compress the data, and chaining to rel...
متن کاملKernel-based data fusion for gene prioritization
MOTIVATION Hunting disease genes is a problem of primary importance in biomedical research. Biologists usually approach this problem in two steps: first a set of candidate genes is identified using traditional positional cloning or high-throughput genomics techniques; second, these genes are further investigated and validated in the wet lab, one by one. To speed up discovery and limit the numbe...
متن کاملOncoScape: Exploring the cancer aberration landscape by genomic data fusion
Although large-scale efforts for molecular profiling of cancer samples provide multiple data types for many samples, most approaches for finding candidate cancer genes rely on somatic mutations and DNA copy number only. We present a new method, OncoScape, which exploits five complementary data types across 11 cancer types to identify new candidate cancer genes. We find many rarely mutated genes...
متن کاملMethods of Genomic Data Fusion: An Overview
The abundance of high-throughput biological data, such as microarray or protein-protein interaction assays has lead to a need for new methods of data analysis, that could infer useful information from large amounts of very noisy and indirect measurements. One solution could be provided by data fusion. Data fusion is a relatively recent term describing machine learning methods that can integrate...
متن کاملA statistical framework for genomic data fusion
MOTIVATION During the past decade, the new focus on genomics has highlighted a particular challenge: to integrate the different views of the genome that are provided by various types of experimental data. RESULTS This paper describes a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature Methods
سال: 2013
ISSN: 1548-7091,1548-7105
DOI: 10.1038/nmeth.2656