Difference between revisions of "Journal:One tool to find them all: A case of data integration and querying in a distributed LIMS platform"

From LIMSWiki
Jump to: navigation, search
(Saving and adding more.)
(Saving and adding more.)
Line 34: Line 34:
  
 
In the past decade, several open-source as well as proprietary LIMS have been developed. Commercial solutions are typically large, complex, and feature-rich products designed to easily support large laboratories. Their license fees can be prohibitive, and extra features may come at additional costs.<ref name="CLIPaper">{{cite web |url=https://www.it.uu.se/edu/course/homepage/lims/vt12/ComprehensiveLaboratoryInformatics.pdf |archiveurl=https://web.archive.org/web/20170825181932/https://www.it.uu.se/edu/course/homepage/lims/vt12/ComprehensiveLaboratoryInformatics.pdf |format=PDF |title=Comprehensive Laboratory Informatics: A Multilayer Approach |author=Wood, S. |publisher=American Laboratory |date=September 2007 |pages=3 |archivedate=25 August 2017}}</ref> To reduce these costs, the last generation of commercial LIMS adopt web-oriented software technologies, particularly the [[Software as a service|software-as-a-service]] distribution model, which reduces the customer’s final expenditure on license fees, hardware, and maintenance. Examples of commercial solutions include [[Abbott Informatics Corporation|STARLIMS]<ref name="AbbottStarlims18">{{cite web |url=https://www.informatics.abbott/us/en/offerings/lims |title=Starlims |publisher=Abbott |date=2018}}</ref>, [[Sapio Sciences, LLC|Exemplar LIMS]]<ref name="SapioSapio18">{{cite web |url=https://www.sapiosciences.com/ |title=Sapio Sciences |publisher=Sapio Sciences, LLC |date=2018}}</ref>, and [[LabVantage Solutions, Inc.|LabVantage]].<ref name="LabVantageLabVantage18">{{cite web |url=https://www.labvantage.com/ |title=LabVantage |publisher=LabVantage Solutions, Inc |date=2018}}</ref>
 
In the past decade, several open-source as well as proprietary LIMS have been developed. Commercial solutions are typically large, complex, and feature-rich products designed to easily support large laboratories. Their license fees can be prohibitive, and extra features may come at additional costs.<ref name="CLIPaper">{{cite web |url=https://www.it.uu.se/edu/course/homepage/lims/vt12/ComprehensiveLaboratoryInformatics.pdf |archiveurl=https://web.archive.org/web/20170825181932/https://www.it.uu.se/edu/course/homepage/lims/vt12/ComprehensiveLaboratoryInformatics.pdf |format=PDF |title=Comprehensive Laboratory Informatics: A Multilayer Approach |author=Wood, S. |publisher=American Laboratory |date=September 2007 |pages=3 |archivedate=25 August 2017}}</ref> To reduce these costs, the last generation of commercial LIMS adopt web-oriented software technologies, particularly the [[Software as a service|software-as-a-service]] distribution model, which reduces the customer’s final expenditure on license fees, hardware, and maintenance. Examples of commercial solutions include [[Abbott Informatics Corporation|STARLIMS]<ref name="AbbottStarlims18">{{cite web |url=https://www.informatics.abbott/us/en/offerings/lims |title=Starlims |publisher=Abbott |date=2018}}</ref>, [[Sapio Sciences, LLC|Exemplar LIMS]]<ref name="SapioSapio18">{{cite web |url=https://www.sapiosciences.com/ |title=Sapio Sciences |publisher=Sapio Sciences, LLC |date=2018}}</ref>, and [[LabVantage Solutions, Inc.|LabVantage]].<ref name="LabVantageLabVantage18">{{cite web |url=https://www.labvantage.com/ |title=LabVantage |publisher=LabVantage Solutions, Inc |date=2018}}</ref>
 +
 +
Commercial LIMS tend to offer features based on common laboratory procedures and best practices, which may not fit highly specific settings well. For instance, LabVantage provides a large set of features, such as sample and batch management, quality control, advanced storage and logistics, and task scheduling. However, the life cycle of xenopatients (i.e., biological models for cancer research based on the transplantation of human tumors in mice) is not available in the standard software and should be implemented as a custom module by the software developer. Another issue that affects commercial LIMSs is the management and standardization of [[Genomics|genomic]] data. To the best of our knowledge, these systems do not exploit any knowledge base related to the genomic data and do not provide any validation and analysis of different genomic data stored in the system.
 +
 +
Other open-source solutions like [[Galaxy (biomedical software)|Galaxy]]<ref name="BlankenbergGalaxy10">{{cite journal |title=Galaxy: a web-based genome analysis tool for experimentalists |journal=Current Protocols in Molecular Biology |author=Blankenberg, D.; Von Kuster, G.; Coraor, N. et al. |year=2010 |volume=19 |issue=Unit 19.10.1–21 |doi=10.1002/0471142727.mb1910s89 |pmid=20069535 |pmc=PMC4264107}}</ref><ref name="GoecksGalaxy10">{{cite journal |title=Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences |journal=Genome Biology |author=Goecks, J.; Nekrutenko, A.; Taylor, J.; The Galaxy Team |year=2010 |volume=11 |issue=8 |pages=R86 |doi=10.1186/gb-2010-11-8-r86 |pmid=20738864 |pmc=PMC2945788}}</ref> focus instead on specific sub-domains, addressing DNA sequencing and annotation, or [[SeqWare]]<ref name="O'ConnorSeqWare10">{{cite journal |journal=BMC Bioinformatics |year=2010 |volume=11 |issue=Suppl. 12 |pages=S2 |title=SeqWare Query Engine: storing and searching sequence data in the cloud |author=O'Connor, B.D.; Merriman, B.; Nelson, S.F. |url=http://www.biomedcentral.com/1471-2105/11/S12/S2 |doi=10.1186/1471-2105-11-S12-S2}}</ref>, which tracks ''in vivo'' and ''in vitro'' experiments and allows for complex analysis workflows.
  
 
==References==
 
==References==

Revision as of 21:54, 20 January 2020

Full article title One tool to find them all: A case of data integration and querying in a distributed LIMS platform
Journal Database
Author(s) Grand, Alberto; Geda, Emanuele; Mignone, Andrea; Bertotti, Andrea; Fiori, Alessandro
Author affiliation(s) Candiolo Cancer Institute, University of Torino
Primary contact Email: alessandro dot fiori at ircc dot it
Year published 2019
Volume and issue 219
Page(s) baz004
DOI 10.1093/database/baz004
ISSN 1758-0463
Distribution license Creative Commons Attribution 4.0 International
Website https://academic.oup.com/database/article/doi/10.1093/database/baz004/5304001
Download https://academic.oup.com/database/article-pdf/doi/10.1093/database/baz004/27643896/baz004.pdf (PDF)

Abstract

In recent years, laboratory information management systems (LIMS) have been growing from mere inventory systems into increasingly comprehensive software platforms, spanning functionalities as diverse as data search, annotation, and analysis. In 2011, our institution started a LIMS project named the Laboratory Assistant Suite with the purpose of assisting researchers throughout all of their laboratory activities, providing graphical tools to support decision-making tasks and building complex analyses on integrated data. The modular architecture of the system exploits multiple databases with different technologies. To provide an efficient and easy tool for retrieving information of interest, we developed the Multi-Dimensional Data Manager (MDDM). By means of intuitive interfaces, scientists can execute complex queries without any knowledge of query languages or database structures, and easily integrate heterogeneous data stored in multiple databases. Together with the other software modules making up the platform, the MDDM has helped improve the overall quality of the data, substantially reduced the time spent with manual data entry and retrieval, and ultimately broadened the spectrum of interconnections among the data, offering novel perspectives to biomedical analysts.

Introduction

The introduction of automation and high-throughput technologies in laboratory environments has raised diverse issues related to the amount and heterogeneity of the data produced, the adoption of robust procedures for sample tracking, and the management of computer-based workflows needed to process and analyze the raw data. Laboratory information management systems (LIMS) have gained increasing popularity because they can ensure good levels of quality control over laboratory activities and efficiently handle the large amounts of data produced.[1]

LIMS aim at assisting the researchers in their daily laboratory practice, improving the accessibility of instruments, and tracking biological samples and their related information.

In the past decade, several open-source as well as proprietary LIMS have been developed. Commercial solutions are typically large, complex, and feature-rich products designed to easily support large laboratories. Their license fees can be prohibitive, and extra features may come at additional costs.[2] To reduce these costs, the last generation of commercial LIMS adopt web-oriented software technologies, particularly the software-as-a-service distribution model, which reduces the customer’s final expenditure on license fees, hardware, and maintenance. Examples of commercial solutions include [[Abbott Informatics Corporation|STARLIMS][3], Exemplar LIMS[4], and LabVantage.[5]

Commercial LIMS tend to offer features based on common laboratory procedures and best practices, which may not fit highly specific settings well. For instance, LabVantage provides a large set of features, such as sample and batch management, quality control, advanced storage and logistics, and task scheduling. However, the life cycle of xenopatients (i.e., biological models for cancer research based on the transplantation of human tumors in mice) is not available in the standard software and should be implemented as a custom module by the software developer. Another issue that affects commercial LIMSs is the management and standardization of genomic data. To the best of our knowledge, these systems do not exploit any knowledge base related to the genomic data and do not provide any validation and analysis of different genomic data stored in the system.

Other open-source solutions like Galaxy[6][7] focus instead on specific sub-domains, addressing DNA sequencing and annotation, or SeqWare[8], which tracks in vivo and in vitro experiments and allows for complex analysis workflows.

References

  1. Chen, Y.; Lin, Y.; Yuan, X. et al.. "Chapter 9: LIMS and Clinical Data Management". In Shen, B.; Tang, H.; Jiang, X.. Translational Biomedical Informatics: A Precision Medicine Perspective. Springer. pp. 225–240. doi:10.1007/978-981-10-1503-8_9. ISBN 9789811015038. 
  2. Wood, S. (September 2007). "Comprehensive Laboratory Informatics: A Multilayer Approach" (PDF). American Laboratory. pp. 3. Archived from the original on 25 August 2017. https://web.archive.org/web/20170825181932/https://www.it.uu.se/edu/course/homepage/lims/vt12/ComprehensiveLaboratoryInformatics.pdf. 
  3. "Starlims". Abbott. 2018. https://www.informatics.abbott/us/en/offerings/lims. 
  4. "Sapio Sciences". Sapio Sciences, LLC. 2018. https://www.sapiosciences.com/. 
  5. "LabVantage". LabVantage Solutions, Inc. 2018. https://www.labvantage.com/. 
  6. Blankenberg, D.; Von Kuster, G.; Coraor, N. et al. (2010). "Galaxy: a web-based genome analysis tool for experimentalists". Current Protocols in Molecular Biology 19 (Unit 19.10.1–21). doi:10.1002/0471142727.mb1910s89. PMC PMC4264107. PMID 20069535. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=PMC4264107. 
  7. Goecks, J.; Nekrutenko, A.; Taylor, J.; The Galaxy Team (2010). "Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences". Genome Biology 11 (8): R86. doi:10.1186/gb-2010-11-8-r86. PMC PMC2945788. PMID 20738864. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=PMC2945788. 
  8. O'Connor, B.D.; Merriman, B.; Nelson, S.F. (2010). "SeqWare Query Engine: storing and searching sequence data in the cloud". BMC Bioinformatics 11 (Suppl. 12): S2. doi:10.1186/1471-2105-11-S12-S2. http://www.biomedcentral.com/1471-2105/11/S12/S2. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. We also added PMCID and DOI when they were missing from the original reference.