Can burrows-Wheeler transform be replaced in chain code compression?

2020 ◽  
Vol 525 ◽  
pp. 109-118
Author(s):  
Borut Žalik ◽  
Domen Mongus ◽  
Niko Lukač ◽  
Krista Rizman Žalik
2019 ◽  
Vol 77 ◽  
pp. 27-36
Author(s):  
Borut Žalik ◽  
Krista Rizman Žalik ◽  
Eva Zupančič ◽  
Niko Lukač ◽  
Mitja Žalik ◽  
...  
Keyword(s):  

Author(s):  
Borut Žalik ◽  
Domen Mongus ◽  
Niko Lukač

2018 ◽  
Vol 439-440 ◽  
pp. 39-49 ◽  
Author(s):  
Borut Žalik ◽  
Domen Mongus ◽  
Niko Lukač ◽  
Krista Rizman Žalik
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Author(s):  
Borut Žalik ◽  
Domen Mongus ◽  
Krista Rizman Žalik ◽  
David Podgorelec ◽  
Niko Lukač
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2016 ◽  
Vol 53 ◽  
pp. 1-10 ◽  
Author(s):  
Borut Žalik ◽  
Domen Mongus ◽  
Krista Rizman Žalik ◽  
Niko Lukač

Informatica ◽  
2021 ◽  
Vol 45 (2) ◽  
Author(s):  
David Podgorelec ◽  
Andrej Nerat ◽  
Borut Žalik
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1998 ◽  
Author(s):  
Charles Lefurgy ◽  
Trevor Mudge
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Author(s):  
William A Freyman ◽  
Kimberly F McManus ◽  
Suyash S Shringarpure ◽  
Ethan M Jewett ◽  
Katarzyna Bryc ◽  
...  

Abstract Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer (DTC) genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale datasets with millions of samples. Furthermore we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for non-commercial use in the code repository https://github.com/23andMe/phasedibd.


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