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A Review of Methods to Quantify the Genomic Similarity of Topological Associating Domains.
- Source :
-
Journal of Computational Biology . Nov2019, Vol. 26 Issue 11, p1326-1338. 13p. - Publication Year :
- 2019
-
Abstract
- Topologically associating domains (TADs) are the most fundamental elements and significant structures of the eukaryotic genome. Currently, algorithms have been developed to find the TADs. But few algorithms are reported to compare the similarity of TADs between genomes. In this study, mice Hi-C sequencing data of four contrasts were enrolled. Seventeen algorithms, including BPscore, Jaccard index (JI) distance, VI distance, image hash, image subtraction, image variance, and so on, were used to quantify the genomic similarity of TADs. Image subtraction, Euclidean distance, and Manhattan distance were significantly better for TAD difference detection than the others. Deferent Hash (dHash) with the best zoom size ranked the second, followed by improved Hamming distance algorithm and JI distance. Advantages and disadvantages of various algorithms for quantifying the similarity of TADs were compared. Our work could provide the fundament for TADs comparison. [ABSTRACT FROM AUTHOR]
- Subjects :
- *EUCLIDEAN distance
*RESEMBLANCE (Philosophy)
*HAMMING distance
Subjects
Details
- Language :
- English
- ISSN :
- 10665277
- Volume :
- 26
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Journal of Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 139564556
- Full Text :
- https://doi.org/10.1089/cmb.2019.0129