The gravitational-wave signature from binary black hole coalescences is an important target for ground-based interferometric detectors such as LIGO and Virgo. The Numerical INJection Analysis (NINJA) project brought together the numerical relativity and gravitational wave data analysis communities, with the goal to optimize the detectability of these events. In its first instantiation, the NINJA project produced a simulated data set with numerical waveforms from binary black hole coalescences of various morphologies (spin, mass ratio, initial conditions), superimposed to Gaussian colored noise at the design sensitivity for initial LIGO and Virgo. We analyzed the NINJA simulated data set with the Q-pipeline algorithm, designed for the all-sky detection of gravitational-wave bursts with minimal assumptions on the shape of the waveform. The algorithm filters the data with a bank of sine-Gaussians, sinusoids with Gaussian envelope, to identify significant excess power in the time-frequency domain. We compared the performance of this burst search algorithm with lalapps_ring, which match-filters data with a bank of ring-down templates to specifically target the final stage of a coalescence of black holes. A comparison of the output of the two algorithms on NINJA data in a single detector analysis yielded qualitatively consistent results; however, due to the low simulation statistics in the first NINJA project, it is premature to draw quantitative conclusions at this stage, and further studies with higher statistics and real detector noise will be needed.