I’m finishing day 2 of the ISME19 Workshop: From Reads to Function. In the session I watched tonight, Mikayla Borton explained components of the DRAM Narrative. The KBase Org for GROW (Genome Resolved Open Watersheds database) was shared with in-person and online participants. Ben pulled in all the MAGs from all samples into one narrative: All Congo Genomes Narrative. The genomes were run through CheckM, DeRep, and DRAM. The narrative had “guiding/scavenger hunt” questions. There were questions about each process. Borton spoke about the product from DRAM. Borton suggested opening all the files to learn about the output. Annotations.tsv has every gene called and annotations for each database used. Each bin has a fasta file that was used as input. Multiple scaffolds may be present. Gene calling information is then listed in different columns, including positions, strandedness. Each of the genes in each annotation is ranked based on the databases used. The metabolism_summary file has different tabs for functions. All the tabs have the same format: the genomes are along columns and the rows have the genes. Participants worked on the narrative and learned about CheckM, DeRep, and DRAM. It was helpful to learn about the information in the output files. Borton used filtering of columns to focus on specific genes or functions. This could be very useful, and I would like to try it for some of the compost metagenomes!
