Literature DB >> 9521934

Kaleidaseq: a Web-based tool to monitor data flow in a high throughput sequencing facility.

N N Dedhia1, W R McCombie.   

Abstract

Tracking data flow in high throughput sequencing is important in maintaining a consistent number of successfully sequenced samples, making decisions on scheduling the flow of sequencing steps, resolving problems at various steps and tracking the status of different projects. This is especially critical when the laboratory is handling a multitude of projects. We have built a Web-based data flow tracking package, called Kaleidaseq, which allows us to monitor the flow and quality of sequencing samples through the steps of preparation of library plates, plaque-picking, preparation of templates, conducting sequencing reactions, loading of samples on gels, base-calling the traces, and calculating the quality of the sequenced samples. Kaleidaseq's suite of displays allows for outstanding monitoring of the production sequencing process. The online display of current information that Kaleidaseq provides on both project status and process queues sorted by project enables accurate real-time assessment of the necessary samples that must be processed to complete the project. This information allows the process manager to allocate future resources optimally and schedule tasks according to scientific priorities. Quality of the sequenced samples can be tracked on a daily basis, which allows the sequencing laboratory to maintain a steady performance level and quickly resolve dips in quality. Kaleidaseq has a simple easy-to-use interface that allows access to all major functions and process queues from one Web page. This software package is modular and designed to allow additional processing steps and new monitoring variables to be added and tracked with ease. Access to the underlying relational database is through the Perl DBI interface, which allows for the use of different relational databases. Kaleidaseq is available for free use by the academic community from http://www.cshl.org/kaleidaseq.

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Year:  1998        PMID: 9521934      PMCID: PMC310700          DOI: 10.1101/gr.8.3.313

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  3 in total

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Authors:  M Boguski; A Chakravarti; R Gibbs; E Green; R M Myers
Journal:  Genome Res       Date:  1996-09       Impact factor: 9.043

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Journal:  Comput Appl Biosci       Date:  1997-04

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Authors:  E Marshall; E Pennisi
Journal:  Science       Date:  1996-04-12       Impact factor: 47.728

  3 in total
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1.  PIMS sequencing extension: a laboratory information management system for DNA sequencing facilities.

Authors:  Peter V Troshin; Vincent Lg Postis; Denise Ashworth; Stephen A Baldwin; Michael J McPherson; Geoffrey J Barton
Journal:  BMC Res Notes       Date:  2011-03-07

2.  Design and implementation of a generalized laboratory data model.

Authors:  Michael C Wendl; Scott Smith; Craig S Pohl; David J Dooling; Asif T Chinwalla; Kevin Crouse; Todd Hepler; Shin Leong; Lynn Carmichael; Mike Nhan; Benjamin J Oberkfell; Elaine R Mardis; LaDeana W Hillier; Richard K Wilson
Journal:  BMC Bioinformatics       Date:  2007-09-26       Impact factor: 3.169

  2 in total

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