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AYB / All Your Base
A base caller for the Illumina Genome Analyzer, using an explicit statistical model of how errors occur during sequencing to produce more accurate reads from the raw intensity data. In contrast to other base-calling approaching, AYB uses a general model of phasing estimated directly from the data rather than assuming that it occurs at a constant rate for all cycles. Dealing with phasing in this manner means that the base calls made by AYB at the end of each read tend to be more accurate than other methods, making greater read lengths feasible and increasing the number of the highest quality reads: AYB returning 2.8 times as many perfect reads than other base callers for 100 cycle data (with smaller gains for shorter reads).
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An efficient basecaller for Illumina sequencers with calibrated quality scores. freeIbis offers significant improvements in sequence accuracy owing to the use of a novel multiclass support vector machine (SVM) algorithm. This approach produces more accurate basecalls than the default Illumina basecaller. freeIbis can use the control sequences to calibrate the output of the SVM to produce directly calibrated quality scores. For instance, freeIbis can produce quality scores that correlate highly with observed ones.
A basecaller for MinION sequencing data. Nanocall provides an offline alternative to Metrichor. On two ecoli and two human samples, with natural as well as PCR-amplified DNA, Nanocall reads have ~68% identity, directly comparable to Metrichor "1D" data. Further, Nanocall is efficient, processing ~500Kbp of sequence per core hour, and fully parallelized. Using 8 cores, Nanocall could basecall a MinION sequencing run in real time. Metrichor provides the ability to integrate the "1D" sequencing of template and complement strands of a single DNA molecule, and create a "2D" read. Nanocall does not currently integrate this technology, and addition of this capability will be an important future development.
Analyzes raw sequencing data from several next generation sequencing (NGS) platforms. MutAid is a pipeline performing six different steps: (i) quality control and filtering; (ii) mapping reads to reference genome; (iii) variant detection, effect prediction and cross-referencing and lastly (iv) and then produces a summary of all information generated. It can be used to interpret mutational variants from various data generated by targeted gene-panel sequencing or whole genome sequencing.
A basecalling method for amplicon pyrosequencing data. Multipass implements a probabilistic framework for working with the raw flowgrams obtained by pyrosequencing. For each sequence variant Multipass calculates the likelihood and nucleotide sequence of several most likely sequences given the flowgram data. This probabilistic approach enables integration of basecalling into a larger model where other parameters can be incorporated, such as the likelihood for observing a full-length open reading frame at the targeted region. Multipass reports useful parameters for estimation of the quality of the called sequence, which allows creation of a high confidence error-free sequence set.
Allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots. Rolexa is based on a base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. It provides probabilistic base calling, quality checks and diagnostic plots for Solexa sequencing data. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. This method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%.
A particle filtering algorithm for base calling in the Illumina’s sequencing-by-synthesis platform. ParticleCall is developed by relying on an HMM representation of the sequencing process. Experimental results demonstrate that the ParticleCall base calling algorithm is more accurate than Bustard, Rolexa, and naiveBayesCall. It is as accurate as BayesCall while being significantly faster. Quality score analysis of the reads indicates that ParticleCall has better discrimination ability than BayesCall, naiveBayesCall and Bustard.
GBS-SNP-CROP / GBS SNP Calling Reference Optional Pipeline
Discovers SNP and characterizes plant germplasm. GBS-SNP-CROP adopts a clustering strategy to build a population-tailored “Mock Reference” from the same GBS data used for downstream SNP calling and genotyping. It may be used to augment the results of alternative analyses, whether or not a reference is available. The tool may complement other reference-based pipelines by extracting more information per sequencing dollar spent. GBS-SNPCROP may be useful even in this case, able to detect large numbers of additional high-quality SNPs missed by the tag-based and read length-restricted approach of TASSEL-GBS.
McSNP Base calling / Melting curve Single nucleotide polymorphism Base calling
Comprises a peak detection procedure and an ordinal regression model. McSNP is a relatively cheap and handy genotyping technique as it is an extension of the reverse transcription-polymerase chain reaction (RT-PCR) technique. It makes use of the difference in melting temperature of PCR products for different alleles. Users and clinicians can conduct the base calling using the default settings directly. A graphical user interface (GUI) is provided for the ease of data manipulation.
A base-caller which opens new avenues for reducing errors significantly in short sequencing reads simply by injecting knowledge from a reference source genome through a base-by-base alignment algorithm. The performance of TOTALRECALLER leads to the conclusion that, by using a Bayesian approach that relies on dynamically creating a reference-based prior, it is possible to significantly lower the error rates of Illumina short reads for both small and large genomes, independent of the sequencing technology used (GAI or GAIIx).
Provides various apps and services run on the EPI2ME operating system which will support the analysis of any living thing, by any user and in any environment. The Metrichor platform is available to users of Oxford Nanopore's MinION - and soon the PromethION. MinION is currently used for the analysis of nucleic acids. Applications made available by Metrichor enable analysis of the resulting experimental data, for example identifying species in a sample by analysing DNA.
A Bayesian method of base calling for Solexa-GA sequencing data. The Bayesian method builds on a hierarchical model that accounts for three sources of noise in the data, which are known to affect the accuracy of the base calls: fading, phasing, and cross-talk between channels. We show that the new method improves the precision of base calling compared with currently leading methods. Furthermore, the proposed method provides a probability score that measures the confidence of each base call. This probability score can be used to estimate the false discovery rate of the base calling or to rank the precision of the estimated DNA sequences, which in turn can be useful for downstream analysis such as sequence alignment.
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