Mutation analysis and variant detection in genetic data

All living things contain a unique sequence of nucleotide bases in their genetic makeup. Mutation is the genetic changes that occur in these sequences. Mutations may cause positive or negative effects in the phenotype, or they may remain neutral and not create any change. Cancer, one of the most dangerous diseases of our age, is uncontrolled cell growth due to mutations in genes and occurs at the cellular level. Mutations have a critical importance in cancer research as they provide information about the causes of cancer formation. With the developing technology, mutations in the DNA sequences can be detected by reading with special devices. Mutation detection processes are very costly applications which require long time. In this study, software solutions were investigated for the detection of small-scale mutations in nucleotide base sequences. Algorithms have been proposed for rapid mutation detection by performing software experiments based on the result of researches. In the study, BRAF (B-Raf protooncogene) gene shared via NCBI (National Center for Biotechnology Information) was used as healthy gene data. The healthy gene information was stored in the Bloom Filter data structure that use hash functions. The DNA sequences of the patients were read in fasta format in accordance with the new generation sequencing methods, and small-scale mutations were successfully detected by comparing them with the healthy data in the filter.