TY - JOUR AU - Yu, Xiaoqing AU - Sun, Shuying PY - 2013 DA - 2013/09/17 TI - Comparing a few SNP calling algorithms using low-coverage sequencing data JO - BMC Bioinformatics SP - 274 VL - 14 IS - 1 AB - Many Single Nucleotide Polymorphism (SNP) calling programs have been developed to identify Single Nucleotide Variations (SNVs) in next-generation sequencing (NGS) data. However, low sequencing coverage presents challenges to accurate SNV identification, especially in single-sample data. Moreover, commonly used SNP calling programs usually include several metrics in their output files for each potential SNP. These metrics are highly correlated in complex patterns, making it extremely difficult to select SNPs for further experimental validations. SN - 1471-2105 UR - https://doi.org/10.1186/1471-2105-14-274 DO - 10.1186/1471-2105-14-274 ID - Yu2013 ER -