Academic Journal
Pattern recognition in lymphoid malignancies using CytoGPS and Mercator.
| Τίτλος: | Pattern recognition in lymphoid malignancies using CytoGPS and Mercator. |
|---|---|
| Συγγραφείς: | Abrams, Zachary B., Tally, Dwayne G., Zhang, Lin, Coombes, Caitlin E., Payne, Philip R. O., Abruzzo, Lynne V., Coombes, Kevin R. |
| Πηγή: | BMC Bioinformatics; 3/1/2021, Vol. 22 Issue 1, p1-12, 12p |
| Θεματικοί όροι: | Pattern recognition systems, Multidimensional databases, Karyotypes, Genetics, Leukemia, Cancer treatment |
| Περίληψη: | Background: There have been many recent breakthroughs in processing and analyzing large-scale data sets in biomedical informatics. For example, the CytoGPS algorithm has enabled the use of text-based karyotypes by transforming them into a binary model. However, such advances are accompanied by new problems of data sparsity, heterogeneity, and noisiness that are magnified by the large-scale multidimensional nature of the data. To address these problems, we developed the Mercator R package, which processes and visualizes binary biomedical data. We use Mercator to address biomedical questions of cytogenetic patterns relating to lymphoid hematologic malignancies, which include a broad set of leukemias and lymphomas. Karyotype data are one of the most common form of genetic data collected on lymphoid malignancies, because karyotyping is part of the standard of care in these cancers. Results: In this paper we combine the analytic power of CytoGPS and Mercator to perform a large-scale multidimensional pattern recognition study on 22,741 karyotype samples in 47 different hematologic malignancies obtained from the public Mitelman database. Conclusion: Our findings indicate that Mercator was able to identify both known and novel cytogenetic patterns across different lymphoid malignancies, furthering our understanding of the genetics of these diseases. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Pattern recognition in lymphoid malignancies using CytoGPS and Mercator. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Abrams%2C+Zachary+B%2E%22">Abrams, Zachary B.</searchLink><br /><searchLink fieldCode="AR" term="%22Tally%2C+Dwayne+G%2E%22">Tally, Dwayne G.</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Lin%22">Zhang, Lin</searchLink><br /><searchLink fieldCode="AR" term="%22Coombes%2C+Caitlin+E%2E%22">Coombes, Caitlin E.</searchLink><br /><searchLink fieldCode="AR" term="%22Payne%2C+Philip+R%2E+O%2E%22">Payne, Philip R. O.</searchLink><br /><searchLink fieldCode="AR" term="%22Abruzzo%2C+Lynne+V%2E%22">Abruzzo, Lynne V.</searchLink><br /><searchLink fieldCode="AR" term="%22Coombes%2C+Kevin+R%2E%22">Coombes, Kevin R.</searchLink> – Name: TitleSource Label: Source Group: Src Data: BMC Bioinformatics; 3/1/2021, Vol. 22 Issue 1, p1-12, 12p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Pattern+recognition+systems%22">Pattern recognition systems</searchLink><br /><searchLink fieldCode="DE" term="%22Multidimensional+databases%22">Multidimensional databases</searchLink><br /><searchLink fieldCode="DE" term="%22Karyotypes%22">Karyotypes</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Leukemia%22">Leukemia</searchLink><br /><searchLink fieldCode="DE" term="%22Cancer+treatment%22">Cancer treatment</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Background: There have been many recent breakthroughs in processing and analyzing large-scale data sets in biomedical informatics. For example, the CytoGPS algorithm has enabled the use of text-based karyotypes by transforming them into a binary model. However, such advances are accompanied by new problems of data sparsity, heterogeneity, and noisiness that are magnified by the large-scale multidimensional nature of the data. To address these problems, we developed the Mercator R package, which processes and visualizes binary biomedical data. We use Mercator to address biomedical questions of cytogenetic patterns relating to lymphoid hematologic malignancies, which include a broad set of leukemias and lymphomas. Karyotype data are one of the most common form of genetic data collected on lymphoid malignancies, because karyotyping is part of the standard of care in these cancers. Results: In this paper we combine the analytic power of CytoGPS and Mercator to perform a large-scale multidimensional pattern recognition study on 22,741 karyotype samples in 47 different hematologic malignancies obtained from the public Mitelman database. Conclusion: Our findings indicate that Mercator was able to identify both known and novel cytogenetic patterns across different lymphoid malignancies, furthering our understanding of the genetics of these diseases. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of BMC Bioinformatics is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1186/s12859-021-03992-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1 Subjects: – SubjectFull: Pattern recognition systems Type: general – SubjectFull: Multidimensional databases Type: general – SubjectFull: Karyotypes Type: general – SubjectFull: Genetics Type: general – SubjectFull: Leukemia Type: general – SubjectFull: Cancer treatment Type: general Titles: – TitleFull: Pattern recognition in lymphoid malignancies using CytoGPS and Mercator. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abrams, Zachary B. – PersonEntity: Name: NameFull: Tally, Dwayne G. – PersonEntity: Name: NameFull: Zhang, Lin – PersonEntity: Name: NameFull: Coombes, Caitlin E. – PersonEntity: Name: NameFull: Payne, Philip R. O. – PersonEntity: Name: NameFull: Abruzzo, Lynne V. – PersonEntity: Name: NameFull: Coombes, Kevin R. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: 3/1/2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 14712105 Numbering: – Type: volume Value: 22 – Type: issue Value: 1 Titles: – TitleFull: BMC Bioinformatics Type: main |
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