CimpleG: finding simple CpG methylation signatures
Abstract DNA methylation signatures are usually based on multivariate approaches that require hundreds of sites for predictions. Here, we propose a computational framework named CimpleG for the detection of small CpG methylation signatures used for cell-type classification and deconvolution. We show...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-07-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13059-023-03000-0 |
| _version_ | 1797778825498591232 |
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| author | Tiago Maié Marco Schmidt Myriam Erz Wolfgang Wagner Ivan G. Costa |
| author_facet | Tiago Maié Marco Schmidt Myriam Erz Wolfgang Wagner Ivan G. Costa |
| author_sort | Tiago Maié |
| collection | DOAJ |
| description | Abstract DNA methylation signatures are usually based on multivariate approaches that require hundreds of sites for predictions. Here, we propose a computational framework named CimpleG for the detection of small CpG methylation signatures used for cell-type classification and deconvolution. We show that CimpleG is both time efficient and performs as well as top performing methods for cell-type classification of blood cells and other somatic cells, while basing its prediction on a single DNA methylation site per cell type. Altogether, CimpleG provides a complete computational framework for the delineation of DNAm signatures and cellular deconvolution. |
| first_indexed | 2024-03-12T23:23:07Z |
| format | Article |
| id | doaj.art-44fe6c4f6b214e30a67685fc48045617 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-03-12T23:23:07Z |
| publishDate | 2023-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-44fe6c4f6b214e30a67685fc480456172023-07-16T11:18:30ZengBMCGenome Biology1474-760X2023-07-0124112810.1186/s13059-023-03000-0CimpleG: finding simple CpG methylation signaturesTiago Maié0Marco Schmidt1Myriam Erz2Wolfgang Wagner3Ivan G. Costa4Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical SchoolHelmholtz Institute for Biomedical Engineering, RWTH Aachen UniversityInstitute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical SchoolHelmholtz Institute for Biomedical Engineering, RWTH Aachen UniversityInstitute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical SchoolAbstract DNA methylation signatures are usually based on multivariate approaches that require hundreds of sites for predictions. Here, we propose a computational framework named CimpleG for the detection of small CpG methylation signatures used for cell-type classification and deconvolution. We show that CimpleG is both time efficient and performs as well as top performing methods for cell-type classification of blood cells and other somatic cells, while basing its prediction on a single DNA methylation site per cell type. Altogether, CimpleG provides a complete computational framework for the delineation of DNAm signatures and cellular deconvolution.https://doi.org/10.1186/s13059-023-03000-0DNA methylationSignature selectionDeconvolutionClinical application |
| spellingShingle | Tiago Maié Marco Schmidt Myriam Erz Wolfgang Wagner Ivan G. Costa CimpleG: finding simple CpG methylation signatures Genome Biology DNA methylation Signature selection Deconvolution Clinical application |
| title | CimpleG: finding simple CpG methylation signatures |
| title_full | CimpleG: finding simple CpG methylation signatures |
| title_fullStr | CimpleG: finding simple CpG methylation signatures |
| title_full_unstemmed | CimpleG: finding simple CpG methylation signatures |
| title_short | CimpleG: finding simple CpG methylation signatures |
| title_sort | cimpleg finding simple cpg methylation signatures |
| topic | DNA methylation Signature selection Deconvolution Clinical application |
| url | https://doi.org/10.1186/s13059-023-03000-0 |
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