Shotgun metagenomics has enabled the discovery of antibiotic resistance genes (ARGs). Although there have been numerous studies benchmarking the bioinformatics methods for shotgun metagenomic data analysis, there has not yet been a study that systematically evaluates the performance of different experimental protocols on metagenomic species profiling and ARG detection. In this study, we generated 35 whole genome shotgun metagenomic sequencing data sets for five samples (three human stool and two microbial standard) using seven experimental protocols (KAPA or Flex kits at 50ng, 10ng, or 5ng input amounts; XT kit at 1ng input amount). Using this comprehensive resource, we evaluated the seven protocols in terms of robust detection of ARGs and microbial abundance estimation at various sequencing depths. We found that the data generated by the seven protocols are largely similar. The inter-protocol variability is significantly smaller than the variability between samples or sequencing depths. We found that a sequencing depth of more than 30M is suitable for human stool samples. A higher input amount (50ng) is generally favorable for the KAPA and Flex kits. This systematic benchmarking study sheds light on the impact of sequencing depth, experimental protocol, and DNA input amount on ARG detection in human stool samples.