CaSpER eliminates noise in the initial expression signal profile by applying sliding window-based median filtering and computing N-level multiscale decomposition at multiple window length scales. The window length increases between consecutive scales so that higher scales correspond to more extensively smoothed signal compared to smaller scales, creating a multi-resolution representation of the expression data. [@serin_harmanci_casper_2020]