Our great sponsors
-
metaGEM
: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
-
InfluxDB
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.
Have you looked into QUAST for comparison of assemblies? How big is the bacterial community? You may need to do some binning of your contigs to separate them into species specific genomes. I can suggest metaGEM (developed by me! should be online in NAR any day now) for generating MAGs for your bacterial species. Although it currently only supports short reads, it may give you an idea of what the bacterial community looks like. Maybe also look into EukCC for estimating fungal genome completeness and/or EukRep for splitting the contigs according to prokaryotic/eukaryotic provenance. You could also try estimating community composition directly from short read analysis using e.g. mOTUs2, kraken/braken, metaphlan, etc.
Have you looked into QUAST for comparison of assemblies? How big is the bacterial community? You may need to do some binning of your contigs to separate them into species specific genomes. I can suggest metaGEM (developed by me! should be online in NAR any day now) for generating MAGs for your bacterial species. Although it currently only supports short reads, it may give you an idea of what the bacterial community looks like. Maybe also look into EukCC for estimating fungal genome completeness and/or EukRep for splitting the contigs according to prokaryotic/eukaryotic provenance. You could also try estimating community composition directly from short read analysis using e.g. mOTUs2, kraken/braken, metaphlan, etc.
Have you looked into QUAST for comparison of assemblies? How big is the bacterial community? You may need to do some binning of your contigs to separate them into species specific genomes. I can suggest metaGEM (developed by me! should be online in NAR any day now) for generating MAGs for your bacterial species. Although it currently only supports short reads, it may give you an idea of what the bacterial community looks like. Maybe also look into EukCC for estimating fungal genome completeness and/or EukRep for splitting the contigs according to prokaryotic/eukaryotic provenance. You could also try estimating community composition directly from short read analysis using e.g. mOTUs2, kraken/braken, metaphlan, etc.
Have you looked into QUAST for comparison of assemblies? How big is the bacterial community? You may need to do some binning of your contigs to separate them into species specific genomes. I can suggest metaGEM (developed by me! should be online in NAR any day now) for generating MAGs for your bacterial species. Although it currently only supports short reads, it may give you an idea of what the bacterial community looks like. Maybe also look into EukCC for estimating fungal genome completeness and/or EukRep for splitting the contigs according to prokaryotic/eukaryotic provenance. You could also try estimating community composition directly from short read analysis using e.g. mOTUs2, kraken/braken, metaphlan, etc.
Our tool: https://github.com/wurmlab/CompareGenomeQualities tries to rank assemblies by balancing different types of biologically relevant information
I would recommend using Merqury to see the completeness and quality of your assembly. https://github.com/marbl/merqury