Here, we performed a benchmarking analysis of five tools for microbe sequence detection using transcriptomics data (Kraken2, MetaPhlAn2, PathSeq, DRAC and Pandora).  Kraken2 was the fastest tool and displayed the second-best sensitivity, though with large variance depending on the species to be classified.  Results from this study support the use of Kraken2 for routine microbiome profiling based on its competitive sensitivity and runtime performance. 
Kraken2
Here, we performed a benchmarking analysis of five tools for microbe sequence detection using transcriptomics data (Kraken2, MetaPhlAn2, PathSeq, DRAC and Pandora).  The sensitivity of MetaPhlAn2 and Pandora was affected by sequence number and DRAC by sequence quality and length.  Nonetheless, we strongly endorse to complement it by combining with MetaPhlAn2 for thorough taxonomic analyses.



MetaPhlAn2
Here, we performed a benchmarking analysis of five tools for microbe sequence detection using transcriptomics data (Kraken2, MetaPhlAn2, PathSeq, DRAC and Pandora).  GATK PathSeq showed the highest sensitivity on average and across all scenarios considered. 
PathSeq
Here, we performed a benchmarking analysis of five tools for microbe sequence detection using transcriptomics data (Kraken2, MetaPhlAn2, PathSeq, DRAC and Pandora).  The sensitivity of MetaPhlAn2 and Pandora was affected by sequence number and DRAC by sequence quality and length.  https://github.com/fjuradorueda/MIME/ and https://github.com/lola4/DRAC/.



DRAC
Here, we performed a benchmarking analysis of five tools for microbe sequence detection using transcriptomics data (Kraken2, MetaPhlAn2, PathSeq, DRAC and Pandora).  The sensitivity of MetaPhlAn2 and Pandora was affected by sequence number and DRAC by sequence quality and length. 
Pandora