NBC: the Naïve Bayes Classification tool webserver for taxonomic classification of metagenomic reads
Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally comple...
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| Published in | Bioinformatics Vol. 27; no. 1; pp. 127 - 129 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Oxford University Press
01.01.2011
International Society for Computational Biology - Oxford University Press |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1367-4803 1367-4811 1460-2059 1367-4811 |
| DOI | 10.1093/bioinformatics/btq619 |
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| Abstract | Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads.
Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss.
Availability: Publicly available at: http://nbc.ece.drexel.edu.
Contact:
gailr@ece.drexel.edu |
|---|---|
| AbstractList | Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads.
Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss.
Availability: Publicly available at: http://nbc.ece.drexel.edu.
Contact: gailr@ece.drexel.edu Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Publicly available at: http://nbc.ece.drexel.edu. Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Availability: Publicly available at: http://nbc.ece.drexel.edu. Contact: gailr@ece.drexel.edu Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads.MOTIVATIONDatasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads.We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss.RESULTSWe introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss.Publicly available at: http://nbc.ece.drexel.edu.AVAILABILITYPublicly available at: http://nbc.ece.drexel.edu. Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign nextgeneration sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Availability: Publicly available at: http://nbc.ece.drexel.edu. Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Availability: Publicly available at: http://nbc.ece.drexel.edu. Contact: gailr@ece.drexel.edu |
| Author | Rosen, Gail L. Rosenfeld, Aaron M. Reichenberger, Erin R. |
| AuthorAffiliation | 1 Department of Electrical and Computer Engineering, 2 School of Biomedical Engineering, Science, and Health Systems and 3 Department of Computer Science, Drexel University, Philadelphia, PA, USA |
| AuthorAffiliation_xml | – name: 1 Department of Electrical and Computer Engineering, 2 School of Biomedical Engineering, Science, and Health Systems and 3 Department of Computer Science, Drexel University, Philadelphia, PA, USA |
| Author_xml | – sequence: 1 givenname: Gail L. surname: Rosen fullname: Rosen, Gail L. organization: 1Department of Electrical and Computer Engineering, 2School of Biomedical Engineering, Science, and Health Systems and 3Department of Computer Science, Drexel University, Philadelphia, PA, USA – sequence: 2 givenname: Erin R. surname: Reichenberger fullname: Reichenberger, Erin R. organization: 1Department of Electrical and Computer Engineering, 2School of Biomedical Engineering, Science, and Health Systems and 3Department of Computer Science, Drexel University, Philadelphia, PA, USA – sequence: 3 givenname: Aaron M. surname: Rosenfeld fullname: Rosenfeld, Aaron M. organization: 1Department of Electrical and Computer Engineering, 2School of Biomedical Engineering, Science, and Health Systems and 3Department of Computer Science, Drexel University, Philadelphia, PA, USA |
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| Snippet | Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still... Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge... |
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| SubjectTerms | Algorithms Applications Note BASIC BIOLOGICAL SCIENCES Bayes Theorem Biochemistry & Molecular Biology Biological and medical sciences Biotechnology & Applied Microbiology Computer Science Fundamental and applied biological sciences. Psychology General aspects High-Throughput Nucleotide Sequencing Internet Mathematical & Computational Biology Mathematics Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Metagenomics - methods Phylogeny Software |
| Title | NBC: the Naïve Bayes Classification tool webserver for taxonomic classification of metagenomic reads |
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