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Conference Paper: A scalable method for cross-platform merging of SNP array datasets

TitleA scalable method for cross-platform merging of SNP array datasets
Authors
KeywordsSNP Array
Scalable Processing
Cross-Platform
Issue Date2013
PublisherScientific Research Publishing.
Citation
The 7th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2013), Beijing, China, 26-28 September 2013. In Engineering, 2013, v. 5 n. 10B, p. 502-508 How to Cite?
AbstractSingle nucleotide polymorphism (SNP) array is a recently developed biotechnology that is extensively used in the study of cancer genomes. The various available platforms make cross-study validations/comparisons difficult. Meanwhile, sample sizes of the studies are fast increasing, which poses a heavy computational burden to even the fastest PC. Here, we describe a novel method that can generate a platform-independent dataset given SNP arrays from multiple platforms. It extracts the common probesets from individual platforms, and performs cross-platform normalizations and summari- zations based on these probesets. Since different platforms may have different numbers of probes per probeset (PPP), the above steps produce preprocessed signals with different noise levels for the platforms. To handle this problem, we adopt a platform-dependent smoothing strategy, and produce a preprocessed dataset that demonstrates uniform noise levels for individual samples. To increase the scalability of the method to a large number of samples, we devised an algorithm that split the samples into multiple tasks, and probesets into multiple segments before submitting to a parallel computing facility. This scheme results in a drastically reduced computation time and increased ability to process ultra- large sample sizes and arrays. © 2013 SciRes.
DescriptionOn this journal issue cover: The 7th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2013)
Open Access Journal
Persistent Identifierhttp://hdl.handle.net/10722/207706
ISSN

 

DC FieldValueLanguage
dc.contributor.authorChen, P-
dc.contributor.authorHung, YS-
dc.date.accessioned2015-01-19T08:41:45Z-
dc.date.available2015-01-19T08:41:45Z-
dc.date.issued2013-
dc.identifier.citationThe 7th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2013), Beijing, China, 26-28 September 2013. In Engineering, 2013, v. 5 n. 10B, p. 502-508-
dc.identifier.issn1947-3931-
dc.identifier.urihttp://hdl.handle.net/10722/207706-
dc.descriptionOn this journal issue cover: The 7th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2013)-
dc.descriptionOpen Access Journal-
dc.description.abstractSingle nucleotide polymorphism (SNP) array is a recently developed biotechnology that is extensively used in the study of cancer genomes. The various available platforms make cross-study validations/comparisons difficult. Meanwhile, sample sizes of the studies are fast increasing, which poses a heavy computational burden to even the fastest PC. Here, we describe a novel method that can generate a platform-independent dataset given SNP arrays from multiple platforms. It extracts the common probesets from individual platforms, and performs cross-platform normalizations and summari- zations based on these probesets. Since different platforms may have different numbers of probes per probeset (PPP), the above steps produce preprocessed signals with different noise levels for the platforms. To handle this problem, we adopt a platform-dependent smoothing strategy, and produce a preprocessed dataset that demonstrates uniform noise levels for individual samples. To increase the scalability of the method to a large number of samples, we devised an algorithm that split the samples into multiple tasks, and probesets into multiple segments before submitting to a parallel computing facility. This scheme results in a drastically reduced computation time and increased ability to process ultra- large sample sizes and arrays. © 2013 SciRes.-
dc.languageeng-
dc.publisherScientific Research Publishing.-
dc.relation.ispartofEngineering-
dc.subjectSNP Array-
dc.subjectScalable Processing-
dc.subjectCross-Platform-
dc.titleA scalable method for cross-platform merging of SNP array datasetsen_US
dc.typeConference_Paperen_US
dc.identifier.emailHung, YS: yshung@hkucc.hku.hk-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.4236/eng.2013.510B103-
dc.identifier.volume5-
dc.identifier.issue10B-
dc.identifier.spage502-
dc.identifier.epage508-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 150119-

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