The potential to rapidly capture the entire microbial community structure or/and gene content makes metagenomic sequencing an attractive tool for pathogen identification and detection of resistance/virulence genes in clinical settings. Here, we assessed the consistency between PCR from a diagnostic laboratory, qPCR from a research laboratory, 16S rRNA gene sequencing and metagenomic shotgun sequencing (MSS) in Clostridium difficile identification in diarrhea stool samples. Twenty-two C. difficile positive diarrhea samples identified by PCR and qPCR and five C. difficile negative diarrhea controls were studied. C. difficile was detected in 90.9% of C. difficile positive samples using 16S rRNA gene sequencing, and 86.3% using MSS. Colony forming units (CFUs) inferred from qPCR analysis were positively correlated with the relative abundance of C. difficile from 16S rRNA gene sequencing (r2=-0.60) and MSS (r2=-0.55). C. difficile was co-detected with Clostridium perfringens, norovirus, sapovirus, parechovirus and anellovirus in 3.7%-27.3% of the samples. A high load of Candida spp was found in a symptomatic control sample in which no causative agents for diarrhea were identified in routine clinical testing. Beta-lactamase and tetracycline resistance genes were the most prevalent (25.9%) antibiotic resistance genes in these samples. In summary, the proof-of-concept study demonstrated that next generation sequencing (NGS) in pathogen detection is moderately correlated with laboratory testing and is advantageous in detecting pathogens without a priori knowledge.