Tucuxi-BLAST: Enabling fast and accurate record linkage of large-scale health-related administrative databases through a DNA-encoded approach

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Tucuxi-BLAST: Enabling fast and accurate record linkage of large-scale health-related administrative databases through a DNA-encoded approach
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Computational tool uses DNA-encoded approach to integrate and analyze different health databases thePeerJ SciReports

). Additionally, to ensure data privacy, an encrypted key containing a random mixture of alphanumeric digits is generated on each Tucuxi-BLAST run. This key is used to encode the strings and numbers in the identification fields into DNA sequences.) to align the sequences between databases. We used the following parameters in Tucuxi-BLAST: megablast and dc-megablast as a task; “-dust no”; “-max_hsps 1”; “-strand plus”; and “-evalue 1e−10”.

Using the Shiny Framework , we also developed the Tucuxi-Tail platform , which facilitates a visual inspection of the record linkage results obtained. This platform first displays identification information from two given records that are potentially the same . Then, users can decide if these two records are the same entity in both databases or not. The Tucuxi-Tail platform was utilized to quickly curate 3,000+ pairs of records, thus generating the gold-standard dataset used in our benchmark.

The classification model was carried out using the BLAST metrics drawn from the comparison between the query sequence and the subject sequence . The metrics utilized in the model were normalized bit-score, mismatch , gapopen , qcovhsp , sstart , and qstart . The normalized bit-score was calculated by dividing the bit-score value between the query and the subject by the best possible bit score value for that same query .

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