Automatic matrix determination in four dye fluorescence‐based DNA sequencing

Yin, Zhongbin; Severin, Jessica; Giddings, Michael C.; Huang, Weian; Westphall, Michael S.; Smith, Lloyd M.

doi:10.1002/elps.1150170626

Cited by 26 publications

(22 citation statements)

References 9 publications

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“…Define Z t;k = ðZ A t;k ; Z C t;k ; Z G t;k ; Z T t;k Þ9 2R 431 , where Z A t;k denotes the concentration (or number) of templates in cluster k with A-terminators at cycle t; the variables Z C t;k ; Z G t;k ; Z T t;k are similarly defined. The spectra of the four fluorophores usually overlap (Yin et al 1996), and this effect can be modeled as…”

Section: From Intensities To Concentrationsmentioning

confidence: 99%

BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing

Kao

Stevens²,

Song³

2009

Genome Res.

102

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Extracting sequence information from raw images of fluorescence is the foundation underlying several high-throughput sequencing platforms. Some of the main challenges associated with this technology include reducing the error rate, assigning accurate base-specific quality scores, and reducing the cost of sequencing by increasing the throughput per run. To demonstrate how computational advancement can help to meet these challenges, a novel model-based base-calling algorithm, BayesCall, is introduced for the Illumina sequencing platform. Being founded on the tools of statistical learning, BayesCall is flexible enough to incorporate various features of the sequencing process. In particular, it can easily incorporate time-dependent parameters and model residual effects. This new approach significantly improves the accuracy over Illumina's base-caller Bustard, particularly in the later cycles of a sequencing run. For 76-cycle data on a standard viral sample, phiX174, BayesCall improves Bustard's average per-base error rate by ;51%. The probability of observing each base can be readily computed in BayesCall, and this probability can be transformed into a useful basespecific quality score with a high discrimination ability. A detailed study of BayesCall's performance is presented here.[Supplemental material is available online at

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Section: From Intensities To Concentrationsmentioning

confidence: 99%

BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing

Kao

Stevens²,

Song³

2009

Genome Res.

102

View full text Add to dashboard Cite

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“…Of these, determination of the cross-talk matrix, which allows for the conversion of mixed-fluorescent signals into concentration estimates for the dye-labeled DNA fragments at a given time point during a sequencing experiment, is likely the most relevant operation (21). Numerous research groups have described methods to determine a representative cross-talk matrix for DNA sequencing data, albeit with limited success (22)(23)(24)(25)(26)(27)(28). For comparison, we present an Applied Biosystems cross-talk matrix for the BigDye v3.1 terminator chemistry derived from a model 377 DNA sequencer ( Table 2) that shows significantly higher off-diagonal values.…”

Section: Pme Technologymentioning

confidence: 99%

Color-blind fluorescence detection for four-color DNA sequencing

Lewis

Haaland

Nguyen

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

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We present an approach called pulsed multiline excitation (PME) for measurements of multicomponent, fluorescence species and demonstrate its application in capillary electrophoresis for DNA sequencing. To fully demonstrate the advantages of PME, a fluorescent dye set has been developed whose absorption maxima span virtually the entire visible spectrum. Unlike emission wavelength-dependent approaches for identifying fluorescent species, the removal of the spectral component in PME confers a number of advantages including higher and normalized signals from all dyes present in the assay, the elimination of spectral cross-talk between dyes, and higher signal collection efficiency. Base-calling is unambiguously determined once dye mobility corrections are made. These advantages translate into significantly enhanced signal quality as illustrated in the primary DNA sequencing data and provide a means for achieving accurate base-calling at lower reagent concentrations.

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“…One of the alternate techniques is to use a typical data set as input to the MatrixFinder program, which determines automatically the best separation matrix. The algorithm that this program is based on was described by us in a separate publication (Yin et al 1996). This program outputs a matrix that can then be used by BaseFinder's matrix application tool.…”

Section: Multicomponent Transformationmentioning

confidence: 99%

“…Another program developed during this period by our group is MatrixFinder, which aids in the visualization and determination of multicomponent separation matrices for multiple color fluorescencebased sequencing (Yin et al 1996). Since publication, the only changes to the program have been a port to OpenStep to increase portability (described below) and some user interface additions.…”

mentioning

confidence: 99%

A Software System for Data Analysis in Automated DNA Sequencing

Giddings¹,

Severin²,

Westphall³

et al. 1998

Genome Res.

Self Cite

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Software for gel image analysis and base-calling in fluorescence-based sequencing consisting of two primary programs, BaseFinder and GelImager, is described. BaseFinder is a framework for trace processing, analysis, and base-calling. BaseFinder is highly extensible, allowing the addition of trace analysis and processing modules without recompilation. Powerful scripting capabilities combined with modularity and multilane handling allow the user to customize BaseFinder to virtually any type of trace processing. We have developed an extensive set of data processing and analysis modules for use with the program in fluorescence-based sequencing. GelImager is a framework for gel image manipulation. It can be used for gel visualization, lane retracking, and as a front end to the Washington University Getlanes program. The programs were designed using a cross-platform development environment, currently allowing them to run in Windows NT, Windows 95, Openstep/Mach, and Rhapsody. Work is ongoing to deploy the software on additional platforms, including Solaris, Linux, and MacOS. This software has been thoroughly tested and debugged in the analysis of >2 million bp of raw sequence data from human chromosome 19 region q13. Overall sequencing accuracy was measured using a significant subset of these data, consisting of ∼600 sequences, by comparing the individual shotgun sequences against the final assembled contigs. Also, results are reported from experiments that analyzed the accuracy of the software and two other well-known base-calling programs for sequencing the M13mp18 vector sequence.[The sequence data described in this paper have been submitted to the GenBank data library under accession no. AF025422]

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Automatic matrix determination in four dye fluorescence‐based DNA sequencing

Cited by 26 publications

References 9 publications

BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing

BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing

Color-blind fluorescence detection for four-color DNA sequencing

A Software System for Data Analysis in Automated DNA Sequencing

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