David Weese

Freie Universität Berlin | FUB · Department of Mathematics and Computer Science

Recent advances in High-Throughput Sequencing demand for novel algorithms working on efficient data structures specifically designed for the analysis of large volumes of sequence data. This chapter describes such data structures, called full-text indexes, to represent all substrings (or substrings up to a certain length) contained in a given text (...

Next-Generation Sequencing (NGS) has revolutionized genomics. NGS technologies produce millions of sequencing reads of a few hundred bases in length. In the following, we focus on NGS reads produced by genome sequencing of a clonal cell population, which has important applications like the de novo genome assembly of previously unknown genomes, for...

Background: The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome Venter et al. (2001) would not have been possible without advanced assembly algorithms and the development of practical BWT based read mappers have been instrumental for NGS analysis. However, ow...

We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly higher sensitivity and precision than existing tools. Its algorithmic core not only reconstructs transcripts ab initio, but also allows the use of the growing annotation o...

High-throughput DNA sequencing has considerably changed the possibilities for conducting biomedical research by measuring billions of short DNA or RNA fragments. A central computational problem, and for many applications a first step, consists of determining where the fragments came from in the original genome. In this article, we review the main t...

We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts with significantly higher sensitivity and precision than existing tools, while competing in speed with the fastest methods. In addition to reconstructing transcripts ab initio, the algorithm also allows...

Motivation: Automatic error correction of high-throughput sequencing data can have a dramatic impact on the amount of usable base pairs and their quality. It has been shown that the performance of tasks such as de novo genome assembly and SNP calling can be dramatically improved after read error correction. While a large number of methods specializ...

Motivation: Next-generation sequencing (NGS) has revolutionized biomedical research in the past decade and led to a continuous stream of developments in bioinformatics, addressing the need for fast and space-efficient solutions for analyzing NGS data. Often researchers need to analyze a set of genomic sequences that stem from closely related speci...

We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a...

Recent advances in sequencing technology allow to produce billions of base pairs per day in the form of reads of length 100 bp an longer and current developments promise the personal $1,000 genome in a couple of years. The analysis of these unprecedented amounts of data demands for efficient data structures and algorithms. One such data structures...

We present in this paper scalable algorithms for optimal string similarity search and join. Our methods are variations of those applied in Masai [15], our recently published tool for mapping high-throughput DNA sequencing data with unpreceded speed and accuracy. The key features of our approach are filtration with approximate seeds and methods for...

We present Masai, a read mapper representing the state-of-the-art in terms of speed and accuracy. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2–4 times faster and more accurate than Bowtie 2 and BWA. The novelties of our read mapper are filtration with approximate seeds and a method for multiple backtracking. Approximate seed...

During the past years, next-generation sequencing has become a key technology for many applications in the biomedical sciences. Throughput continues to increase and new protocols provide longer reads than currently available. In almost all applications, read mapping is a first step. Hence, it is crucial to have algorithms and implementations that p...

We present Masai, a read mapper representing the state of the art in terms of speed and sensitivity. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2--3 times faster and more accurate than Bowtie 2 and BWA. The novelties of our read mapper are filtration with approximate seeds and a method for multiple backtracking. Approximate...

The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map. Here we present a method for 'split' read mapping, where prefix and su...

Large-scale comparison of genomic sequences requires reliable tools for the search of local alignments. Practical local aligners are in general fast, but heuristic, and hence sometimes miss significant matches. We present here the local pairwise aligner STELLAR that has full sensitivity for ε-alignments, i.e. guarantees to report all local alignmen...

Second generation sequencing technologies yield DNA sequence data at ultra high-throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. The assessment of the quality of read mapping results is not straightforward and has not been formalized so far. Hence, it has not bee...

Deep sequencing has become the method of choice for determining the small RNA content of a cell. Mapping the sequenced reads onto their reference genome serves as the basis for all further analyses, namely for identification and quantification. A method frequently used is Mega BLAST followed by several filtering steps, even though it is slow and in...

Second-generation sequencing technologies deliver DNA sequence data at unprecedented high throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. Due to the large amounts of data, efficient algorithms and implementations are crucial for this task. We present an efficien...

Novel high-throughput sequencing technologies pose new algorithmic challenges in handling massive amounts of short-read, high-coverage data. A robust and versatile consensus tool is of particular interest for such data since a sound multi-read alignment is a prerequisite for variation analyses, accurate genome assemblies and insert sequencing. A mu...

Variable order Markov chains (VOMCs) are a flexible class of models that extend the well-known Markov chains. They have been applied to a variety of problems in computational biology, e.g. protein family classification. A linear time and space construction algorithm has been published in 2000 by Apostolico and Bejerano. However, neither a report of...

Many multiple sequence alignment tools have been developed in the past, progressing either in speed or alignment accuracy. Given the importance and wide-spread use of alignment tools, progress in both categories is a contribution to the community and has driven research in the field so far. We introduce a graph-based extension to the consistency-ba...

We propose a general approach for frequency based string mining, which has many applications, e.g. in contrast data mining. Our contribution is a novel algorithm based on a deferred data structure. Despite its simplicity, our approach is up to 4 times faster and uses about half the memory compared to the best-known algorithm of Fischer et al. Appli...

The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome 1 would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between st...

Listings. The listings show C++ code that uses SeqAn to implement a simplified version of the well-known MUMmer tool [8].

Any segmentation approach assumes certain knowledge concerning data modalities, relevant organs and their imaging characteristics. These assumptions are necessary for developing criteria by which to separate the organ in question from the surrounding tissue. Typical assumptions are that the organs have homogeneous gray-value characteristics (region...