Jabba: hybrid error correction for long sequencing reads using maximal exact matches

Third generation sequencing platforms produce longer reads with higher error rates than second generation sequencing technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes. Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned. In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data. Unique to our method is that this mapping is constructed with a seed and extend methodology, using maximal exact matches as seeds. In addition to benchmark results, certain theoretical results concerning the possibilities and limitations of the use of maximal exact matches in the context of third generation reads are presented

High Performance P3M N-body code: CUBEP3M

This paper presents CUBEP3M, a publicly-available high performance cosmological N-body code and describes many utilities and extensions that have been added to the standard package. These include a memory-light runtime SO halo finder, a non-Gaussian initial conditions generator, and a system of unique particle identification. CUBEP3M is fast, its accuracy is tuneable to optimize speed or memory, and has been run on more than 27,000 cores, achieving within a factor of two of ideal weak scaling even at this problem size. The code can be run in an extra-lean mode where the peak memory imprint for large runs is as low as 37 bytes per particles, which is almost two times leaner than other widely used N-body codes. However, load imbalances can increase this requirement by a factor of two, such that fast configurations with all the utilities enabled and load imbalances factored in require between 70 and 120 bytes per particles. CUBEP3M is well designed to study large scales cosmological systems, where imbalances are not too large and adaptive time-stepping not essential. It has already been used for a broad number of science applications that require either large samples of non-linear realizations or very large dark matter N-body simulations, including cosmological reionization, halo formation, baryonic acoustic oscillations, weak lensing or non-Gaussian statistics. We discuss the structure, the accuracy, known systematic effects and the scaling performance of the code and its utilities, when applicable.Comment: 20 pages, 17 figures, added halo profiles, updated to match MNRAS accepted versio

CalFUSE v3: A Data-Reduction Pipeline for the Far Ultraviolet Spectroscopic Explorer

Since its launch in 1999, the Far Ultraviolet Spectroscopic Explorer (FUSE) has made over 4600 observations of some 2500 individual targets. The data are reduced by the Principal Investigator team at the Johns Hopkins University and archived at the Multimission Archive at Space Telescope (MAST). The data-reduction software package, called CalFUSE, has evolved considerably over the lifetime of the mission. The entire FUSE data set has recently been reprocessed with CalFUSE v3.2, the latest version of this software. This paper describes CalFUSE v3.2, the instrument calibrations upon which it is based, and the format of the resulting calibrated data files.Comment: To appear in PASP; 29 pages, 13 figures, uses aastex, emulateap

DUDE-Seq: Fast, Flexible, and Robust Denoising for Targeted Amplicon Sequencing

We consider the correction of errors from nucleotide sequences produced by next-generation targeted amplicon sequencing. The next-generation sequencing (NGS) platforms can provide a great deal of sequencing data thanks to their high throughput, but the associated error rates often tend to be high. Denoising in high-throughput sequencing has thus become a crucial process for boosting the reliability of downstream analyses. Our methodology, named DUDE-Seq, is derived from a general setting of reconstructing finite-valued source data corrupted by a discrete memoryless channel and effectively corrects substitution and homopolymer indel errors, the two major types of sequencing errors in most high-throughput targeted amplicon sequencing platforms. Our experimental studies with real and simulated datasets suggest that the proposed DUDE-Seq not only outperforms existing alternatives in terms of error-correction capability and time efficiency, but also boosts the reliability of downstream analyses. Further, the flexibility of DUDE-Seq enables its robust application to different sequencing platforms and analysis pipelines by simple updates of the noise model. DUDE-Seq is available at http://data.snu.ac.kr/pub/dude-seq

Circular polarization measurement in millimeter-wavelength spectral-line VLBI observations

This paper considers the problem of accurate measurement of circular polarization in imaging spectral-line VLBI observations in the lambda=7 mm and lambda=3 mm wavelength bands. This capability is especially valuable for the full observational study of compact, polarized SiO maser components in the near-circumstellar environment of late-type, evolved stars. Circular VLBI polarimetry provides important constraints on SiO maser astrophysics, including the theory of polarized maser emission transport, and on the strength and distribution of the stellar magnetic field and its dynamical role in this critical circumstellar region. We perform an analysis here of the data model containing the instrumental factors that limit the accuracy of circular polarization measurements in such observations, and present a corresponding data reduction algorithm for their correction. The algorithm is an enhancement of existing spectral line VLBI polarimetry methods using autocorrelation data for calibration, but with innovations in bandpass determination, autocorrelation polarization self-calibration, and general optimizations for the case of low SNR, as applicable at these wavelengths. We present an example data reduction at $\lambda=7$ mm and derive an estimate of the predicted accuracy of the method of m_c < 0.5% or better at lambda=7 mm and m_c < 0.5-1% or better at lambda=3 mm. Both the strengths and weaknesses of the proposed algorithm are discussed, along with suggestions for future work.Comment: 23 pages, 13 figure