期刊
BIOINFORMATICS
卷 33, 期 14, 页码 I261-I266出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btx271
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资金
- National Science Foundation Graduate Research Fellowship [DGE1255832]
- National Science Foundation ABI Innovation Grant [DBI1564466]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1564466] Funding Source: National Science Foundation
Motivation: Recent experiments have provided Hi-C data at resolution as high as 1 kbp. However, 3D structural inference from high-resolution Hi-C datasets is often computationally unfeasible using existing methods. Results: We have developed miniMDS, an approximation of multidimensional scaling (MDS) that partitions a Hi-C dataset, performs high-resolution MDS separately on each partition, and then reassembles the partitions using low-resolution MDS. miniMDS is faster, more accurate, and uses less memory than existing methods for inferring the human genome at high resolution (10 kbp).
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