Single-sensor color cameras primarily form images through a color filter array laid over the sensor. The acquired raw data represent a single color component per pixel and usually undergo demosaicking to form fully defined color images. This, however, produces artifacts that may affect the performance of low-level processing tasks applied to such estimated images. We instead propose to directly use raw data to estimate the image partial derivatives for edge detection. Considering luminance- and color-based approaches based on Deriche filters, we show that schemes using raw data may provide as accurate edge detection results as classical demosaicking-based ones at much reduced computational cost.