Objective：To investigate effects of methods of pre-processing and variant filtering on variant recognition in analyzing whole exome sequencing data. Methods：Through the calculation of depth of coverage（DP），number of variants，transition/transversion and non-reference concordance，we compared the effects of different pre-processing methods（FASTX-Toolkit，Trimmomatic and non treat－ment） and strategies of single-end（SE） inclusion and ‘Hard’ filter and variants quality score recalibration（VQSR） on variants call－ing in variants filter using whole exome sequencing data from two test samples. Results：Trimmomatic pre-processed reads showed similar DP to reads without pre-processing，but significantly higher than that of FASTX-Toolkit pre-processed reads. With DP ≥10× and genotype quality（GQ）≥20，number of called single nucleotide variants（SNV） identified by Trimmomatic was greater than that identified by FASTX-Toolkit，but similar to that without pre-processing. With the inclusion of SE，number of variants increased signif－icantly for FASTX-Toolkit pre-processing（28%） than Trimmomatic pre-processing（5%）. In the all settings，‘Hard’ filtering filtered less SNVs than VQSR filtering in small sample size. Conclusions：Sequence reads are trimmed and/or filtered moderately by Trim－momatic，whereas they seemed to be over-filtered by FASTX-Toolkit. Keeping the SE is good for variants recognition in the down－stream analysis. The ‘Hard’ filtering showed a more favorable tolerability profile than ‘VQSR’ filtering.