Accurate detection of drug resistance is the key to guide effective TB treatment. While genotypic resistance can be quickly detected by molecular methods, their application was challenged by mycobacteria population mix comprising both susceptible and resistant cells (heteroresistance). For this, the next-generation sequencing (NGS) based approach promised variant determination even at low frequencies. However, an accurate method for detecting low frequency valid NGS variants in the current data is lacking.
To solve this problem, we developed a tool that allows the detection of variants binoSNP determination of low-frequency single-nucleotide polymorphisms (SNPs) in NGS datasets of Mycobacterium tuberculosis complex (MTBC) strains. By taking the reference-mapped file as input, evaluate each position of the genome binoSNP interesting using binomial test procedure. binoSNP validated using in-silico, in vitro, and patient isolates series dataset consisting of various depths genome coverage (100-500 ×) and the SNP allele frequency (1-30%). Overall, the SNP detection limits for low frequency depending on the combination of depth of coverage and allele frequencies associated resistance mutations. binoSNP allows for the detection of SNPs associated resistance force at a frequency of 1% with ≥400 × coverage. In conclusion, binoSNP provide a valid approach for detecting low frequency SNP-mediated resistance in NGS Data from clinical MTBC strains. It can be implemented in a friendly analysis tool automatically, the end user to the data NGS and is a step toward individualized TB treatment
Genetic factors (gene mutation) causes a variety of neurological disease is rare and unusual. Identification of the underlying mutation in neurodegenerative diseases is very important because of the heterogeneous nature of the genome and different clinical manifestations. Early and accurate diagnosis for patients with neurodegenerative molecular cardinal undergo the appropriate treatment regimen.
Next-generation sequencing methods (NGS) examines millions of sequences at a time. Consequently, the molecular diagnosis of rare, previously served with the “unknown cause”, it is now possible in a short time. This method produces a large amount of data that can be utilized in the management of patients. Because each person has a unique genome, NGS has changed the diagnostic and therapeutic strategies in individual genome sequencing and mapping.
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