rapmad: Robust analysis of peptide microarray data
<p>Abstract</p> <p>Background</p> <p>Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2011-08-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/12/324 |
| _version_ | 1819115531168382976 |
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| author | Rothermel Andrée Reimer Ulf Kühne Yvonne Löwer Martin Renard Bernhard Y Türeci Özlem Castle John C Sahin Ugur |
| author_facet | Rothermel Andrée Reimer Ulf Kühne Yvonne Löwer Martin Renard Bernhard Y Türeci Özlem Castle John C Sahin Ugur |
| author_sort | Rothermel Andrée |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R.</p> <p>Results</p> <p>We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments.</p> <p>Conclusions</p> <p>rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from <url>http://www.tron-mz.de/compmed</url>.</p> |
| first_indexed | 2024-12-22T05:02:40Z |
| format | Article |
| id | doaj.art-d94523cb980b438f9b771c9203b53c51 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-22T05:02:40Z |
| publishDate | 2011-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-d94523cb980b438f9b771c9203b53c512022-12-21T18:38:14ZengBMCBMC Bioinformatics1471-21052011-08-0112132410.1186/1471-2105-12-324rapmad: Robust analysis of peptide microarray dataRothermel AndréeReimer UlfKühne YvonneLöwer MartinRenard Bernhard YTüreci ÖzlemCastle John CSahin Ugur<p>Abstract</p> <p>Background</p> <p>Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R.</p> <p>Results</p> <p>We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments.</p> <p>Conclusions</p> <p>rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from <url>http://www.tron-mz.de/compmed</url>.</p>http://www.biomedcentral.com/1471-2105/12/324 |
| spellingShingle | Rothermel Andrée Reimer Ulf Kühne Yvonne Löwer Martin Renard Bernhard Y Türeci Özlem Castle John C Sahin Ugur rapmad: Robust analysis of peptide microarray data BMC Bioinformatics |
| title | rapmad: Robust analysis of peptide microarray data |
| title_full | rapmad: Robust analysis of peptide microarray data |
| title_fullStr | rapmad: Robust analysis of peptide microarray data |
| title_full_unstemmed | rapmad: Robust analysis of peptide microarray data |
| title_short | rapmad: Robust analysis of peptide microarray data |
| title_sort | rapmad robust analysis of peptide microarray data |
| url | http://www.biomedcentral.com/1471-2105/12/324 |
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