RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets

摘要: Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for analysis microbial communities both scientifically diagnostically. The biggest challenge is extraction relevant information from huge sequence datasets generated studies. Although plethora tools are available, data still bottleneck. To overcome bottleneck analysis, we developed an automated computational workflow called RIEMS – Reliable Information Extraction Metagenomic Sequence datasets. assigns every individual read within dataset taxonomically cascading different analyses with decreasing stringency assignments using various software applications. After completion analyses, results summarised in clearly structured result protocol organised taxonomically. high accuracy performance were proven comparison other simulated has potential to fill gap that exists regard usefulness power genuine was demonstrated early version 2011 when it used detect orthobunyavirus sequences leading discovery Schmallenberg virus.