We take a quantitative approach in estimating the impact of the errors in sequences on analysis using BLAST. We apply fault injection to measure the errors in the analysis by emulating sequence errors in the query and studying its BLAST output. False negatives are the matches that are omitted in the output because of faults in the sequence. Our experiments show that a small rate (0.002) of deletion fault can generate a false negative error rate of 0.388. The false negative rate is higher than the false positive rate. Since false negatives cannot be reduced by "filtering" mechanisms such as reciprocal BLAST, they exacerbate the impact of sequencing errors. Fault injection has been demonstrated effective in analyzing the impact of sequencing errors on analyses and in increasing the dependability of other computational approaches in biology.