Read mapping, which involves computationally in-tensive approximate string matching (ASM) on large datasets, is the primary performance bottleneck in genome sequence analysis. To accelerate read mapping, a processing-in-memory (PIM) architecture that conducts highly parallel computations within the memory to reduce energy-inefficient data movements can be a promising solution. In this paper, we present ReTAP, a processing-in-ReRAM Bitap accelerator for genomic analysis. Instead of using the intricate dynamic programming algorithm, our design incorporates the Bitap algorithm, which uses only simple bitwise operations to perform ASM. Additionally, we explore the opportunity to reduce redundant computations by dynamically adjusting the error tolerance of Bitap and co-design the hardware to enhance computation parallelism. Our evaluation demonstrates that ReTAP outperforms GenASM, the state-of-the-art Bitap accelerator, with a 153.7 x higher throughput.