A framework for counting alleles in computational clouds
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1312Keywords:
Big Data, Computational Clouds, HLA allelesAbstract
Objective: develop a framework to carry out anthropological comparisons, classify alleles, infer the waiting time of patients requiring transplantation, among other analyses. Method: comparison of donor and patient alleles using a search algorithm to, based on allele counts, perform analysis. To reduce analysis execution time, queries were optimized and parallelized, allowing their efficient execution in computing clouds. Results: the framework is capable of performing analysis in seconds, even on a database that contains more than 5 million records. Conclusion: the proposed framework has the potential to help clinicians/researchers obtain information to improve the organ donation process among unrelated donors.
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