Efficient Maximal Repeat Finding Using the Burrows-Wheeler Transform and Wavelet Tree

2012 ◽  
Vol 9 (2) ◽  
pp. 421-429 ◽  
Author(s):  
M. Oguzhan Kulekci ◽  
Jeffrey Scott Vitter ◽  
Bojian Xu
Keyword(s):  
Maximal Repeat ◽  
Burrows Wheeler Transform

scholarly journals Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform

2020 ◽  
Author(s):  
William A Freyman ◽  
Kimberly F McManus ◽  
Suyash S Shringarpure ◽  
Ethan M Jewett ◽  
Katarzyna Bryc ◽  
...  
Keyword(s):  
Isolation By Distance ◽  
False Negative ◽  
Segment Length ◽  
Data Sets ◽  
Haplotype Sharing ◽  
Binary File ◽  
Inference Algorithms ◽  
Out Of Sample ◽  
Massive Scale ◽  
Burrows Wheeler Transform

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.

Faster short-read mapping with strobemer seeds in syncmer space

2021 ◽  
Author(s):  
Kristoffer Sahlin
Keyword(s):  
High Speed ◽  
Mapping Accuracy ◽  
Original Sequence ◽  
Short Read ◽  
Short Read Mapping ◽  
Alignment Algorithms ◽  
Reverse Complement ◽  
Short Read Aligner ◽  
Candidate Regions ◽  
Burrows Wheeler Transform

Short-read genome alignment is a fundamental computational step used in many bioinformatic analyses. It is therefore desirable to align such data as fast as possible. Most alignment algorithms consider a seed-and-extend approach. Several popular programs perform the seeding step based on the Burrows-Wheeler Transform with a low memory footprint, but they are relatively slow compared to more recent approaches that use a minimizer-based seeding-and-chaining strategy. Recently, syncmers and strobemers were proposed for sequence comparison. Both protocols were designed for improved conservation of matches between sequences under mutations. Syncmers is a thinning protocol proposed as an alternative to minimizers, while strobemers is a linking protocol for gapped sequences and was proposed as an alternative to k-mers. The main contribution in this work is a new seeding approach that combines syncmers and strobemers. We use a strobemer protocol (randstrobes) to link together syncmers (i.e., in syncmer-space) instead of over the original sequence. Our protocol allows us to create longer seeds while preserving mapping accuracy. A longer seed length reduces the number of candidate regions which allows faster mapping and alignment. We also contribute the insight that speed-wise, this protocol is particularly effective when syncmers are canonical. Canonical syncmers can be created for specific parameter combinations and reduce the computational burden of computing the non-canonical randstrobes in reverse complement. We implement our idea in a proof-of-concept short-read aligner strobealign that aligns short reads 3-4x faster than minimap2 and 15-23x faster than BWA and Bowtie2. Many implementation versions of, e.g., BWA, achieve high speed on specific hardware. Our contribution is algorithmic and requires no hardware architecture or system-specific instructions. Strobealign is available at https://github.com/ksahlin/StrobeAlign.

scholarly journals A secure image steganography based on burrows wheeler transform and dynamic bit embedding

2019 ◽  
Vol 9 (1) ◽  
pp. 460
Author(s):  
Ahmed Toman Thahab
Keyword(s):  
Communication Networks ◽  
Color Image ◽  
Image Steganography ◽  
Digital Data ◽  
Embedding Capacity ◽  
Image Size ◽  
Secret Data ◽  
Exclusive Or ◽  
Burrows Wheeler Transform ◽  
Color Image Steganography

In modern public communication networks, digital data is massively transmitted through the internet with a high risk of data piracy. Steganography is a technique used to transmit data without arousing suspicion of secret data existence.  In this paper, a color image steganography technique is proposed in spatial domain. The cover image is segmented into non-overlapping blocks which are scattered among image size window using Burrows Wheeler transform before embedding. Secret data is embedded in each block according to its sequence in the Burrows Wheeler transform output. The hiding method is an operation of an exclusive-or between a virtual bit which is generated from the most significant bit and the least significant bits of the cover pixel. Results of the algorithm are analyzed according to its degradation of the output image and embedding capacity. The results are also compared with other existing methods.

scholarly journals A New Burrows Wheeler Transform Markov Distance

2020 ◽  
Vol 34 (04) ◽  
pp. 5444-5453
Author(s):  
Edward Raff ◽  
Charles Nicholas ◽  
Mark McLean
Keyword(s):  
Dna Sequence ◽  
Distance Measure ◽  
Feature Vector ◽  
Distance Metrics ◽  
Prior Work ◽  
Compression Algorithms ◽  
Fixed Length ◽  
Malware Classification ◽  
Classification Tasks ◽  
Burrows Wheeler Transform

Prior work inspired by compression algorithms has described how the Burrows Wheeler Transform can be used to create a distance measure for bioinformatics problems. We describe issues with this approach that were not widely known, and introduce our new Burrows Wheeler Markov Distance (BWMD) as an alternative. The BWMD avoids the shortcomings of earlier efforts, and allows us to tackle problems in variable length DNA sequence clustering. BWMD is also more adaptable to other domains, which we demonstrate on malware classification tasks. Unlike other compression-based distance metrics known to us, BWMD works by embedding sequences into a fixed-length feature vector. This allows us to provide significantly improved clustering performance on larger malware corpora, a weakness of prior methods.

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