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AKT: Ancestry and Kinship Toolkit
[article]
2016
bioRxiv
pre-print
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Ancestry and Kinship Toolkit(AKT) is a statistical genetics tool for analysing large cohorts of whole-genome sequenced samples. It can rapidly detect related samples, characterise sample ancestry, calculate correlation between variants, check Mendel consistency and perform data clustering. AKT brings together the functionality of many state-of-the-art methods, with a focus on speed and a unified interface. We believe it will be an invaluable tool for the curation of large WGS data-sets.
doi:10.1101/047829
fatcat:nr32ggmksnbalhuxzwjda3jvny
Stochastic Petri Nets in Systems Biology
2005
BMC Bioinformatics
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AKT: ancestry and kinship toolkit
2016
Bioinformatics
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Motivation: Ancestry and Kinship Toolkit (AKT) is a statistical genetics tool for analysing large cohorts of whole-genome sequenced samples. It can rapidly detect related samples, characterise sample ancestry, calculate correlation between variants, check Mendel consistency and perform data clustering. AKT brings together the functionality of many state-of-the-art methods, with a focus on speed and a unified interface. We believe it will be an invaluable tool for the curation of large WGS
doi:10.1093/bioinformatics/btw576
pmid:27634946
fatcat:glajxbvc6nezroyxkwadkzztty
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... ets. Availability: The source code is available at https://illumina.
BEETL-fastq: a searchable compressed archive for DNA reads
[article]
2014
arXiv
pre-print
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Motivation: FASTQ is a standard file format for DNA sequencing data which stores both nucleotides and quality scores. A typical sequencing study can easily generate hundreds of gigabytes of FASTQ files, while public archives such as ENA and NCBI and large international collaborations such as the Cancer Genome Atlas can accumulate many terabytes of data in this format. Text compression tools such as gzip are often employed to reduce the storage burden, but have the disadvantage that the data
arXiv:1406.4376v1
fatcat:k2n33cm34be4jpfknal5ca7eum
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... be decompressed before it can be used. Here we present BEETL-fastq, a tool that not only compresses FASTQ-formatted DNA reads more compactly than gzip, but also permits rapid search for k-mer queries within the archived sequences. Importantly, the full FASTQ record of each matching read or read pair is returned, allowing the search results to be piped directly to any of the many standard tools that accept FASTQ data as input. Results: We show that 6.6 terabytes of human reads in FASTQ format can be transformed into 1.7 terabytes of indexed files, from where we can search for 1, 10, 100, 1000, a million of 30-mers in respectively 3, 8, 14, 45 and 567 seconds plus 20 ms per output read. Useful applications of the search capability are highlighted, including the genotyping of structural variant breakpoints and "in silico pull-down" experiments in which only the reads that cover a region of interest are selectively extracted for the purposes of variant calling or visualization. Availability: BEETL-fastq is part of the BEETL library, available as a github repository at git@github.com:BEETL/BEETL.git.
NxTrim: optimized trimming of Illumina mate pair reads
[article]
2014
bioRxiv
pre-print
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Motivation:Mate pair protocols add to the utility of paired-end sequencing by boosting the genomic distance spanned by each pair of reads, potentially allowing larger repeats to be bridged and resolved. The Illumina Nextera Mate Pair (NMP) protocol employs a circularisation-based strategy that leaves behind 38bp adapter sequences which must be computationally removed from the data. While "adapter trimming" is a well-studied area of bioinformatics, existing tools do not fully exploit the
doi:10.1101/007666
fatcat:clvwz3di3bhcrb3cqemrtp6x2y
more »
... ar properties of NMP data and discard more data than is necessary.Results:We present NxTrim, a tool that strives to discard as little sequence as possible from NMP reads. The sequence either side of the adapter site is triaged into "virtual libraries" of mate pairs, paired-end reads and single-ended reads. When combined, these data boost coverage and can substantially improve the de novo assembly of bacterial genomes.
NxRepair: error correction inde novosequence assembly using Nextera mate pairs
2015
PeerJ
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Cox and Ole Schulz-Trieglaff are permanent employees of Illumina Inc., a public company that develops and markets systems for genomic analysis. They receive shares as part of their compensation. ...
Murphy, Jared O'Connell and Ole Schulz-Trieglaff conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared ...
doi:10.7717/peerj.996
pmid:26056623
pmcid:PMC4458127
fatcat:hmtzadvoifgwppno2idsjx6egy
Rapid Genotype Refinement for Whole-Genome Sequencing Data using Multi-Variate Normal Distributions
[article]
2015
bioRxiv
pre-print
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Whole-genome low-coverage sequencing has been combined with linkage-disequilibrium (LD) based genotype refinement to accurately and cost-effectively infer genotypes in large cohorts of individuals. Most genotype refinement methods are based on hidden Markov models, which are accurate but computationally expensive. We introduce an algorithm that models LD using a simple multivariate Gaussian distribution. The key feature of our algorithm is its speed, it is hundreds of times faster than other
doi:10.1101/031484
fatcat:cijympiozvc6nbzuh3rvmwfody
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... hods on the same data set and its scaling behaviour is linear in the number of samples. We demonstrate the performance of the method on both low-coverage and high-coverage samples.
LC-MSsim - a simulation software for Liquid Chromatography Mass Spectrometry data
2008
BMC Bioinformatics
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Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are the detection of peptide features in
doi:10.1186/1471-2105-9-423
pmid:18842122
pmcid:PMC2577660
fatcat:jqubcnbko5fczchifarnx3ccm4
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... e mass spectra and the alignment of samples by correcting for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists only for peptide identification algorithms but no data that represents a ground truth for the evaluation of feature detection, alignment and filtering algorithms. Results: We present LC-MSsim, a simulation software for LC-ESI-MS experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS data set using a predictor for the retention time of the peptides and a model for peak shapes and elution profiles of the mass spectral peaks. Our software also offers the possibility to add contaminants, to change the background noise level and includes a model for the detectability of peptides in mass spectra. After the simulation, LC-MSsim writes the simulated data to mzData, a public XML format. The software also stores the positions (monoisotopic m/z and retention time) and ion counts of the simulated ions in separate files. Conclusion: LC-MSsim generates simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm developers can match the results of feature detection and alignment algorithms against the simulated ion lists and meaningful error rates can be computed. We anticipate that LC-MSsim will be useful to the wider community to perform benchmark studies and comparisons between computational tools.
Statistical quality assessment and outlier detection for liquid chromatography-mass spectrometry experiments
2009
BioData Mining
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Quality assessment methods, that are common place in engineering and industrial production, are not widely spread in large-scale proteomics experiments. But modern technologies such as Multi-Dimensional Liquid Chromatography coupled to Mass Spectrometry (LC-MS) produce large quantities of proteomic data. These data are prone to measurement errors and reproducibility problems such that an automatic quality assessment and control become increasingly important. Results: We propose a methodology to
doi:10.1186/1756-0381-2-4
pmid:19351414
pmcid:PMC2678124
fatcat:2i6eozvkznc2xcul2ve3cz6xgy
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... assess the quality and reproducibility of data generated in quantitative LC-MS experiments. We introduce quality descriptors that capture different aspects of the quality and reproducibility of LC-MS data sets. Our method is based on the Mahalanobis distance and a robust Principal Component Analysis. Conclusion: We evaluate our approach on several data sets of different complexities and show that we are able to precisely detect LC-MS runs of poor signal quality in large-scale studies.
NxTrim: optimized trimming of Illumina mate pair reads: Table 1
2015
Bioinformatics
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Motivation: Mate pair protocols add to the utility of paired-end sequencing by boosting the genomic distance spanned by each pair of reads, potentially allowing larger repeats to be bridged and resolved. The Illumina Nextera Mate Pair (NMP) protocol uses a circularization-based strategy that leaves behind 38-bp adapter sequences, which must be computationally removed from the data. While 'adapter trimming' is a well-studied area of bioinformatics, existing tools do not fully exploit the
doi:10.1093/bioinformatics/btv057
pmid:25661542
fatcat:y3pfkah4ujh27k2egwaubfgoji
more »
... ar properties of NMP data and discard more data than is necessary. Results: We present NxTrim, a tool that strives to discard as little sequence as possible from NMP reads. NxTrim makes full use of the sequence on both sides of the adapter site to build 'virtual libraries' of mate pairs, paired-end reads and single-ended reads. For bacterial data, we show that aggregating these datasets allows a single NMP library to yield an assembly whose quality compares favourably to that obtained from regular paired-end reads. Availability and implementation: The source code is available at https://github.com/sequencing/ NxTrim
metaBEETL: high-throughput analysis of heterogeneous microbial populations from shotgun DNA sequences
2013
BMC Bioinformatics
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Environmental shotgun sequencing (ESS) has potential to give greater insight into microbial communities than targeted sequencing of 16S regions, but requires much higher sequence coverage. The advent of next-generation sequencing has made it feasible for the Human Microbiome Project and other initiatives to generate ESS data on a large scale, but computationally efficient methods for analysing such data sets are needed. Here we present metaBEETL, a fast taxonomic classifier for environmental
doi:10.1186/1471-2105-14-s5-s2
pmid:23734710
pmcid:PMC3622627
fatcat:bakccnlzlzglpkosw6c6x3whgq
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... tgun sequences. It uses a Burrows-Wheeler Transform (BWT) index of the sequencing reads and an indexed database of microbial reference sequences. Unlike other BWT-based tools, our method has no upper limit on the number or the total size of the reference sequences in its database. By capturing sequence relationships between strains, our reference index also allows us to classify reads which are not unique to an individual strain but are nevertheless specific to some higher phylogenetic order. Tested on datasets with known taxonomic composition, metaBEETL gave results that are competitive with existing similarity-based tools: due to normalization steps which other classifiers lack, the taxonomic profile computed by metaBEETL closely matched the true environmental profile. At the same time, its moderate running time and low memory footprint allow metaBEETL to scale well to large data sets. Code to construct the BWT indexed database and for the taxonomic classification is part of the BEETL library, available as a github repository at git@github.com:BEETL/BEETL.git.
Manta: Rapid detection of structural variants and indels for clinical sequencing applications
[article]
2015
bioRxiv
pre-print
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Summary: We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid clinical analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50x genomic coverage is analyzed in less than 20 minutes. Manta can discover and score variants
doi:10.1101/024232
fatcat:mphs2xtgrbdffdekoe7lcsiily
more »
... sed on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to basepair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. Availability: Manta source code and Linux binaries are available from http://github.com/Illumina/manta. Contact: csaunders@illumina.com
Computational Quantification of Peptides from LC-MS Data
2008
Journal of Computational Biology
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Ole Schulz-Trieglaff is supported by the Max Planck Research School for Computational Biology and Scientific Computing in Berlin. ...
In Schulz-Trieglaff et al. (2007) , we have shown that we can accurately and quickly quantify even low abundance peptides using a mother wavelet that mimics the distribution of isotopic peak intensities ...
doi:10.1089/cmb.2007.0117
pmid:18707556
fatcat:vmu57z3b3vc7xgicgfdr6ezrxu
OpenMS – An open-source software framework for mass spectrometry
2008
BMC Bioinformatics
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Mass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available
doi:10.1186/1471-2105-9-163
pmid:18366760
pmcid:PMC2311306
fatcat:ydzwiuwdhfff5k2xj4iaglslde
more »
... oday, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow. Results: We present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.
A geometric approach for the alignment of liquid chromatography—mass spectrometry data
2007
Computer applications in the biosciences : CABIOS
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Several algorithms exist for this task, such as Li et al. (2003) , Schulz-Trieglaff et al. (2007) and Wang et al. (2003) . ...
The charge of each feature is determined by fitting a theoretical isotope model based on the average composition of a peptide for a given mass as proposed earlier (Schulz-Trieglaff et al., 2007) . ...
doi:10.1093/bioinformatics/btm209
pmid:17646306
fatcat:5hcddxjpbzafbf77fhpeu7r6n4
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