Substitution matrix based color schemes for sequence alignment visualization
Abstract Background Visualization of multiple sequence alignments often includes colored symbols, usually characters encoding amino acids, according to some (physical) properties, such as hydrophobicity or charge. Typically, color schemes are created manually, so that equal or similar colors are ass...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-05-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-020-3526-6 |
| _version_ | 1818244002873344000 |
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| author | Patrick Kunzmann Benjamin E. Mayer Kay Hamacher |
| author_facet | Patrick Kunzmann Benjamin E. Mayer Kay Hamacher |
| author_sort | Patrick Kunzmann |
| collection | DOAJ |
| description | Abstract Background Visualization of multiple sequence alignments often includes colored symbols, usually characters encoding amino acids, according to some (physical) properties, such as hydrophobicity or charge. Typically, color schemes are created manually, so that equal or similar colors are assigned to amino acids that share similar properties. However, this assessment is subjective and may not represent the similarity of symbols very well. Results In this article we propose a different approach for color scheme creation: We leverage the similarity information of a substitution matrix to derive an appropriate color scheme. Similar colors are assigned to high scoring pairs of symbols, distant colors are assigned to low scoring pairs. In order to find these optimal points in color space a simulated annealing algorithm is employed. Conclusions Using the substitution matrix as basis for a color scheme is consistent with the alignment, which itself is based on the very substitution matrix. This approach allows fully automatic generation of new color schemes, even for special purposes which have not been covered, yet, including schemes for structural alphabets or schemes that are adapted for people with color vision deficiency. |
| first_indexed | 2024-12-12T14:10:06Z |
| format | Article |
| id | doaj.art-de5b1fdd4b5a419897191a2f82a9acc4 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-12T14:10:06Z |
| publishDate | 2020-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-de5b1fdd4b5a419897191a2f82a9acc42022-12-22T00:22:07ZengBMCBMC Bioinformatics1471-21052020-05-0121111210.1186/s12859-020-3526-6Substitution matrix based color schemes for sequence alignment visualizationPatrick Kunzmann0Benjamin E. Mayer1Kay Hamacher2Department of Computational Biology and Simulation, TU DarmstadtDepartment of Computational Biology and Simulation, TU DarmstadtDepartment of Computational Biology and Simulation, TU DarmstadtAbstract Background Visualization of multiple sequence alignments often includes colored symbols, usually characters encoding amino acids, according to some (physical) properties, such as hydrophobicity or charge. Typically, color schemes are created manually, so that equal or similar colors are assigned to amino acids that share similar properties. However, this assessment is subjective and may not represent the similarity of symbols very well. Results In this article we propose a different approach for color scheme creation: We leverage the similarity information of a substitution matrix to derive an appropriate color scheme. Similar colors are assigned to high scoring pairs of symbols, distant colors are assigned to low scoring pairs. In order to find these optimal points in color space a simulated annealing algorithm is employed. Conclusions Using the substitution matrix as basis for a color scheme is consistent with the alignment, which itself is based on the very substitution matrix. This approach allows fully automatic generation of new color schemes, even for special purposes which have not been covered, yet, including schemes for structural alphabets or schemes that are adapted for people with color vision deficiency.http://link.springer.com/article/10.1186/s12859-020-3526-6Open sourcePythonColor spaceOptimizationSequence alignment |
| spellingShingle | Patrick Kunzmann Benjamin E. Mayer Kay Hamacher Substitution matrix based color schemes for sequence alignment visualization BMC Bioinformatics Open source Python Color space Optimization Sequence alignment |
| title | Substitution matrix based color schemes for sequence alignment visualization |
| title_full | Substitution matrix based color schemes for sequence alignment visualization |
| title_fullStr | Substitution matrix based color schemes for sequence alignment visualization |
| title_full_unstemmed | Substitution matrix based color schemes for sequence alignment visualization |
| title_short | Substitution matrix based color schemes for sequence alignment visualization |
| title_sort | substitution matrix based color schemes for sequence alignment visualization |
| topic | Open source Python Color space Optimization Sequence alignment |
| url | http://link.springer.com/article/10.1186/s12859-020-3526-6 |
| work_keys_str_mv | AT patrickkunzmann substitutionmatrixbasedcolorschemesforsequencealignmentvisualization AT benjaminemayer substitutionmatrixbasedcolorschemesforsequencealignmentvisualization AT kayhamacher substitutionmatrixbasedcolorschemesforsequencealignmentvisualization |