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An open-source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing
Celina Montemayor1, Alexandra Simone1, James Long2
1Department of Transfusion Medicine, NIH Clinical Center, Bethesda, MD, USA.
Vox Sanguinis
|February 10, 2021
Summary
DTM-Tools software accurately predicts Kell, Duffy, and Kidd blood group antigens from exome sequencing data, aiding transfusion medicine. This open-source tool enhances existing clinical data for improved blood group interpretation.
Area of Science:
- Genomics
- Transfusion Medicine
- Bioinformatics
Background:
- Next-generation sequencing (NGS) offers significant potential in transfusion medicine.
- Exome sequencing (ES) is becoming standard in clinical practice.
- Blood group interpretation can be derived from existing ES data.
Purpose of the Study:
- To introduce DTM-Tools, an open-source software for blood group antigen prediction from ES data.
- To validate the software's performance using three blood group systems.
Main Methods:
- The DTM-Tools algorithm analyzed 1018 ES NGS files.
- Predictions were correlated with serology for 5 antigens in 108 samples.
- Discrepancies were investigated using alternative phenotyping and genotyping methods, including long-read NGS.
Main Results:
- DTM-Tools identified known KEL, FY, and JK alleles and additional variants in KEL, ACKR1, and SLC14A1.
- Software predictions showed high concordance with serology.
- Discrepancies were attributed to clerical errors, weak antigen expression, or novel variants.
Conclusions:
- DTM-Tools enables rapid blood group antigen prediction from ES data.
- Software predictions were accurate, even in cases of discrepancies.
- DTM-Tools is an open-source, continuously developing resource for transfusion medicine.
