Software Error Correction Research Articles

CARE 2.0: reducing false-positive sequencing error corrections using machine learning

BackgroundNext-generation sequencing pipelines often perform error correction as a preprocessing step to obtain cleaned input data. State-of-the-art error correction programs are able to reliably detect and correct the majority of sequencing errors. However, they also introduce new errors by making false-positive corrections. These correction mistakes can have negative impact on downstream analysis, such as k-mer statistics, de-novo assembly, and variant calling. This motivates the need for more precise error correction tools.ResultsWe present CARE 2.0, a context-aware read error correction tool based on multiple sequence alignment targeting Illumina datasets. In addition to a number of newly introduced optimizations its most significant change is the replacement of CARE 1.0’s hand-crafted correction conditions with a novel classifier based on random decision forests trained on Illumina data. This results in up to two orders-of-magnitude fewer false-positive corrections compared to other state-of-the-art error correction software. At the same time, CARE 2.0 is able to achieve high numbers of true-positive corrections comparable to its competitors. On a simulated full human dataset with 914M reads CARE 2.0 generates only 1.2M false positives (FPs) (and 801.4M true positives (TPs)) at a highly competitive runtime while the best corrections achieved by other state-of-the-art tools contain at least 3.9M FPs and at most 814.5M TPs. Better de-novo assembly and improved k-mer analysis show the applicability of CARE 2.0 to real-world data.ConclusionFalse-positive corrections can negatively influence down-stream analysis. The precision of CARE 2.0 greatly reduces the number of those corrections compared to other state-of-the-art programs including BFC, Karect, Musket, Bcool, SGA, and Lighter. Thus, higher-quality datasets are produced which improve k-mer analysis and de-novo assembly in real-world datasets which demonstrates the applicability of machine learning techniques in the context of sequencing read error correction. CARE 2.0 is written in C++/CUDA for Linux systems and can be run on the CPU as well as on CUDA-enabled GPUs. It is available at https://github.com/fkallen/CARE.

Improving lexical errors in EFL writing by using software-mediated corrective feedback

This research aims at revisiting the role of software when it comes to providing learners with corrective feedback on their pieces of writing. The study, based on the analysis of handwritten and software-corrected versions of essays written by 33 undergraduate students enrolled in the undergraduate degree programme in English Studies at a Spanish University contributed to confirming the assumption that technology can indeed be a useful tool in the teaching and learning process. More specifically, this study demonstrated that students could reduce significantly the number of lexical errors in their essays through the autonomous use of error-correction software and that, over time, the students can improve on their ability to avoid such errors. Nevertheless, the study has also confirmed that software can in no way completely replace teachers, as computer programming is quite limited and there are errors that only proficient language users can detect and correct.

Improvement of identification methods for honeybee specific Lactic Acid Bacteria; future approaches.

Honeybees face many parasites and pathogens and consequently rely on a diverse set of individual and group-level defenses to prevent disease. The crop microbiota of Apis mellifera, composed of 13 Lactic Acid Bacterial (LAB) species within the genera Lactobacillus and Bifidobacterium, form a beneficial symbiotic relationship with each other and the honeybee to protect their niche and their host. Possibly playing a vital role in honeybee health, it is important that these honeybee specific Lactic Acid Bacterial (hbs-LAB) symbionts can be correctly identified, isolated and cultured, to further investigate their health promoting properties. We have previously reported successful identification to the strain level by culture-dependent methods and we recently sequenced and annotated the genomes of the 13 hbs-LAB. However, the hitherto applied techniques are unfortunately very time consuming, expensive and not ideal when analyzing a vast quantity of samples. In addition, other researchers have constantly failed to identify the 13 hbs-LAB from honeybee samples by using inadequate media and/or molecular techniques based on 16S rRNA gene sequencing with insufficient discriminatory power. The aim of this study was to develop better and more suitable methods for the identification and cultivation of hbs-LAB. We compared currently used bacterial cultivation media and could for the first time demonstrate a significant variation in the hbs-LAB basic requirements for optimal growth. We also present a new bacterial identification approach based on amplicon sequencing of a region of the 16S rRNA gene using the Illumina platform and an error correction software that can be used to successfully differentiate and rapidly identify the 13 hbs-LAB to the strain level.

QuorUM: An Error Corrector for Illumina Reads

MotivationIllumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.ResultsWe produce trimmed and error-corrected reads that result in assemblies with longer contigs and fewer errors. We compared QuorUM against several published error correctors and found that it is the best performer in most metrics we use. QuorUM is efficiently implemented making use of current multi-core computing architectures and it is suitable for large data sets (1 billion bases checked and corrected per day per core). We also demonstrate that a third-party assembler (SOAPdenovo) benefits significantly from using QuorUM error-corrected reads. QuorUM error corrected reads result in a factor of 1.1 to 4 improvement in N50 contig size compared to using the original reads with SOAPdenovo for the data sets investigated.AvailabilityQuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.Contact gmarcais@umd.edu.

Efficient Software-Based Encoding and Decoding of BCH Codes

Error correction software for Bose-Chaudhuri-Hochquenghem (BCH) codes is optimized for general purpose processors that do not equip hardware for Galois field arithmetic. The developed software applies parallelization with a table lookup method to reduce the number of iterations, and maximum parallelization under a cache size limitation is sought for a high throughput implementation. Since this method minimizes the number of lookup tables for encoding and decoding processes, a large parallel factor can be chosen for a given cache size. The naive word length of a general purpose CPU is used as a whole by employing the developed mask elimination method. The tradeoff of the algorithm complexity and the regularity is examined for several syndrome generation methods, which leads to a simple error detection scheme that reuses the encoder and a simplified syndrome generation method requiring only a small number of Galois field multiplications. The parallel factor for Chien search is increased much by transforming the error locator polynomial so that it contains symmetric exponents of positive and negative signs. The experimental results demonstrate that the developed software cannot only provide sufficient throughput for real-time error correction of NAND flash memory in embedded systems but also enhance the reliability of file systems in general purpose computers.

Simulation of the errors transfer in an articulation-type coordinate measuring machine

It is necessary to study the transferring effect of every error resource of a coordinate measuring system. This paper gives quantitative analysis of the transferring effects of parameter errors in a non-perpendicular coordinate measuring system. A typical articulation-type coordinate measuring system is analyzed which combines six angle encoders and three measuring arms and one stylus. The measuring equation of this system is given and the error-transferring model is derived from this equation. As the systematic errors of the parameters of the system are given beforehand, simulated computation is carried out on the error-transferring model of this articulation-type coordinate measuring system. The effects of parameter errors on the position of the stylus of the coordinate measuring system are clearly seen from the simulation results. These make the software error correction of the coordinate measuring system possible and will also provide the base for error correction of the system.

Active profiling and polishing for efficient control of material removal from large precision surfaces with moderate asphericity

We present the development of an active fabrication technology for controlling material removal on large precision surfaces of moderate departure from a sphere. The underlying philosophy was established as an efficient solution to the challenging problem of fabricating secondary mirrors of up to nominally 2.5 m in diameter for modern 8 m class telescopes and beyond. The facility described comprises a CNC profiler, two contact profilometers, and a full size active polisher. The trial work-piece was a convex surface of 830 mm in diameter on a zero-expansion ceramic (`Cervit') blank – a 1/3 scale hyperbolic mirror for a proposed 2.5 m diameter f/7 secondary mirror for the 8 m Gemini telescope. Using software error-correction from profilometric metrology data, a factor of 2 improvement in generating the convex aspheric profile was achieved. An active loose-abrasive polishing process is also described, in which a full-size tool is configured to deliver variable, edgeless, sub-diameter removal-footprints. Real-time monitoring of process variables is described, and approximately 10% convergence in each polishing pass is reported.

Durability evaluation of software error correction on a machining center

Machine tool software error correction has been successfully demonstrated in laboratories for at least the last 20 years. However, no results could be found that evaluate the durability of such an approach. To be cost beneficial for industry, the time consuming measurement procedure needs to be as infrequent as possible. This study attempts to quantify the durability of such an approach on a commercial 3-Axis machining center. A traditional correction model is created and implemented inside the control system along with a first order thermal correction of the scales. Measurements are made with the Laser Ball Bar, which minimizes data collection to less than 30 min. The compensation system was evaluated over a 9 month period in which the machine experienced normal machining and common mishaps (tool crash). The results show that during this 9 month period, the compensation system was still capable of significantly reducing the machine's inherent errors.

New error correction algorithms minimizing residual positional error for a computer integrated error calibration/correction system in computer numerically controlled machine tools

Linear displacement accuracy is one of the most important factors determining machine tool performance. Software error correction has been generally used for improving the positional accuracy in computer numerically controlled (CNC) machine tools. In this paper, a set of new correction algorithms has been presented for minimizing residual positional errors in CNC machine tools after correction.

New error correction algorithms minimizing residual positional error for a computer integrated error calibration/correction system in computer numerically controlled machine tools

Linear displacement accuracy is one of the most important factors determining machine tool performance. Software error correction has been generally used for improving the positional accuracy in computer numerically controlled (CNC) machine tools. In this paper, a set of new correction algorithms has been presented for minimizing residual positional errors in CNC machine tools after correction.

Self-calibration method and software error correction for three-dimensional coordinate measuring machines using artefact measurements

The proposed self-calibration method uses an artefact, a ball plate, for error identification. Unlike other methods this ball plate need not be calibrated, i.e. the distances between the different balls on the plate need not be known accurately. After measurement of the ball plate in different positions within the measuring volume, the systematic geometrical errors, like scale errors, axes' pitch, yaw and non-orthogonality, of the geometric error model of the measuring machine can be calculated. This geometrical error model is used afterwards by the software error correction to correct on-line every single measurement carried by the measuring machine. This results in a higher accuracy of the measurement. As an example, the self-calibration method has been carried out on a CNC 3-D coordinate measuring machine and the resulting software error correction has been evaluated using step-gauge measurements. The results of the evaluation show that the systematic geometrical errors are greatly reduced.

Improving the Accuracy of Angle Measurement System with Optical Grating

A new angle measurement system with optical grating is presented in the paper. Its distinguishing features are: (1) Gratings having sine function transmissivity are used as the index gratings. The harmonic errors of the Moire fringes are greatly reduced. (2) Errors caused by zero offsets, inequality in amplitude and nonorthogonality in phase of two Moire fringe signals are corrected by real time software error correction. (3) Four unequally spaced reading heads are used to eliminate the errors caused by the graduation error of optical grating and error motions of the spindle. The experimental device gives an accuracy about 0.2 arcseconds.

Error Diagnosis and Compensation Using Kinematic Models and Position Error Data

A method is described in this paper for obtaining values of coefficients in a kinematic model can be developed Next, the kinematic modal is fitted to position data. Then, coefficients of the model are analyzed so that a diagnosis of the source of errors in the mechanism can be made The results can be used for mechanical or software error correction of machine tools, robots, linkages in sensing mechanisms, etc.