MetaQuast for assembling samples from complex communities

• metaGEM

  14 165 6.3 Python

  :gem: An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data

In my experience I haven’t found metaquast or other assembly evaluation tools very useful precisely because they are geared toward reference genome based assessment. I don’t think there is a standardized way of assessing your assemblies (someone please correct me if I’m wrong), but it helps to look at the distribution of contig lengths. For example, an assembly with a distribution peak around 10kbp is much better than a peak around 1kbp. In your case you probably want to bin the assembled contigs into MAGs and then assess the quality of those genomes using a tool like CheckM or BUSCO. If you want to get an idea of tools/workflows you can use then maybe check out the metaGEM pipeline on GitHub or read the paper

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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