The American team at the Broad Institute in Boston (USA) has developed the SMA Finder, a new algorithm designed to identify SMA more easily from data generated by high-throughput sequencing (NGS):
- raw sequencing data from gene panels, exomes and whole genomes were collected by the Broad Institute in collaboration with the Estonian Department of Genetics and the UK National Sequence Bank,
- which corresponded to controls,
- the false-positive rate was extremely low (1 in 200,000),
- 29 genuine cases of SMA were diagnosed, some of which were known and others had been mistaken for limb-girdle muscular dystrophy.
At the end of this study, carried out on a very large number of samples, SMA Finder proved to be much more effective and reliable than previous computer tools of this type for detecting SMA.