University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019-UMR 8204-CIIL-Centre d'Infection et d'Immunité de Lille, F-59000, Lille, France.
PEGASE-Biosciences, Institut Pasteur de Lille, 1 Rue du Professeur Calmette, 59019, Lille, France.
Genome Biol. 2017 Dec 19;18(1):233. doi: 10.1186/s13059-017-1367-z.
The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.
可用序列数据的增加推动了微生物学领域的发展；然而，如果没有生物信息学技能，要理解这些数据仍然是有问题的。我们描述了 MICRA，这是一个自动管道，作为一个网络界面，可通过读取分析进行微生物鉴定和特征描述。MICRA 使用迭代映射来识别基因和变体，以对抗参考基因组。其他模块允许预测抗生素敏感性和耐药性，并比较几个样本的结果。MICRA 速度很快，与当前方法相比，产生的假阳性注释和变体调用很少，因此它是充分利用测序数据的一个非常有趣的工具。
