rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data
Background Recent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosom...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer (Biomed Central Ltd.)
2012
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| Online Access: | http://hdl.handle.net/1721.1/69629 |
| _version_ | 1826211146336567296 |
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| author | Kim, Tae-Min Luquette, Lovelace J. Xi, Ruibin Park, Peter J. |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Kim, Tae-Min Luquette, Lovelace J. Xi, Ruibin Park, Peter J. |
| author_sort | Kim, Tae-Min |
| collection | MIT |
| description | Background
Recent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosomal alterations would allow a detailed characterization of the cancer genome with unprecedented accuracy.
Results
We develop a method for identification of copy number alterations in a tumor genome compared to its matched control, based on application of Smith-Waterman algorithm to single-end sequencing data. In a performance test with simulated data, our algorithm shows >90% sensitivity and >90% precision in detecting a single copy number change that contains approximately 500 reads for the normal sample. With 100-bp reads, this corresponds to a ~50 kb region for 1X genome coverage of the human genome. We further refine the algorithm to develop rSW-seq, (recursive Smith-Waterman-seq) to identify alterations in a complex configuration, which are commonly observed in the human cancer genome. To validate our approach, we compare our algorithm with an existing algorithm using simulated and publicly available datasets. We also compare the sequencing-based profiles to microarray-based results.
Conclusion
We propose rSW-seq as an efficient method for detecting copy number changes in the tumor genome. |
| first_indexed | 2024-09-23T15:01:39Z |
| format | Article |
| id | mit-1721.1/69629 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:01:39Z |
| publishDate | 2012 |
| publisher | Springer (Biomed Central Ltd.) |
| record_format | dspace |
| spelling | mit-1721.1/696292022-09-29T12:07:39Z rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data Kim, Tae-Min Luquette, Lovelace J. Xi, Ruibin Park, Peter J. Harvard University--MIT Division of Health Sciences and Technology Park, Peter J. Park, Peter J. Background Recent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosomal alterations would allow a detailed characterization of the cancer genome with unprecedented accuracy. Results We develop a method for identification of copy number alterations in a tumor genome compared to its matched control, based on application of Smith-Waterman algorithm to single-end sequencing data. In a performance test with simulated data, our algorithm shows >90% sensitivity and >90% precision in detecting a single copy number change that contains approximately 500 reads for the normal sample. With 100-bp reads, this corresponds to a ~50 kb region for 1X genome coverage of the human genome. We further refine the algorithm to develop rSW-seq, (recursive Smith-Waterman-seq) to identify alterations in a complex configuration, which are commonly observed in the human cancer genome. To validate our approach, we compare our algorithm with an existing algorithm using simulated and publicly available datasets. We also compare the sequencing-based profiles to microarray-based results. Conclusion We propose rSW-seq as an efficient method for detecting copy number changes in the tumor genome. National Institute of General Medical Sciences (U.S.) (R01 GM082798) 2012-03-09T18:19:38Z 2012-03-09T18:19:38Z 2010-08 2009-12 Article http://purl.org/eprint/type/JournalArticle 1471-2105 http://hdl.handle.net/1721.1/69629 Kim, Tae-Min et al. “rSW-seq: Algorithm for Detection of Copy Number Alterations in Deep Sequencing Data.” BMC Bioinformatics 11.1 (2010): 432. Web. 9 Mar. 2012. en_US http://dx.doi.org/10.1186/1471-2105-11-432 BMC Bioinformatics Creative Commons Attribution http://creativecommons.org/licenses/by/2.0 application/pdf Springer (Biomed Central Ltd.) BioMed Central |
| spellingShingle | Kim, Tae-Min Luquette, Lovelace J. Xi, Ruibin Park, Peter J. rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title | rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title_full | rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title_fullStr | rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title_full_unstemmed | rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title_short | rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data |
| title_sort | rsw seq algorithm for detection of copy number alterations in deep sequencing data |
| url | http://hdl.handle.net/1721.1/69629 |
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