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Running the NMDC Workflows in NMDC EDGE Tutorials

NMDC EDGE QuickStart

For more information on how to start running the workflows, visit the How-to Guide for Running Workflows. The following is a set of questions and answers to increase familiarity with the workflows and their outputs. To view answers, click on the dropdown arrow next to "Answer".

Answer This is an example of the answer dropdown.



NMDC EDGE QuickStart Tutorial Practice

Task 1: Create an NMDC EDGE account with your ORCiD information.

Task 2: Download the small interleaved data file listed here. (Note: This is paired-end data with the pairs interleaved together into a single file.) Upload the file to NMDC EDGE.

Task 3 (optional): Click on "My Profile". Edit your account to receive email notification of project status by clicking “ON”.

Metagenomics

ReadsQC

NMDC EDGE Metagenome ReadsQC Tutorial Practice

Task: Log into NMDC EDGE and run the Metagenome ReadsQC workflow using the dataset uploaded in the QuickStart tutorial. When the run has finished, answer the questions below using the workflow results.

  • Question 1: How many reads were in the input file? How many bases were in the input file?

    Answer

    Input file contained 4,496,774 reads and 674,516,100 bases.

  • Question 2: How many reads were in the output file? How many bases were in the output file?

    Answer

    Output contained 3,353,438 reads and 487,250,239 bases.

  • Question 3: Which output file would you then use as the input for a subsequent workflow if you wanted QC'ed data?

    Answer

    For this project, the clean, filtered data is in the output file called SRR7877884-int-0.1.filtered.gz.

Read-based Taxonomy Classification

NMDC EDGE Metagenome Read-based Taxonomy Classification Tutorial Practice

Task: Run the Metagenome Read-based Taxonomy Classification workflow with all three taxonomy classification tools. (Note: All three tools are selected by default. While a user can opt to turn off one or two tools, it is recommended to run all three.) Use the clean data output file from the project run in the ReadsQC Tutorial. When the run finishes, answer the questions below using the workflow outputs.

  • Question 1: How many of the Top 10 species are identified by more than one tool?

    Answer

    There are seven species called by more than one taxonomy tool: Pseudomonas aeruginosa, Salmonella enterica, Listeria monocytogenes, Enterococcus faecalis, Lactobacillus fermentum, Bacillus subtilis, and Escherichia coli.

  • Question 2: List the genera that are identified by all three tools within the Top 10.

    Answer

    There are four genera called by all three taxonomy classification tools: Pseudomonas, Bacillus, Enterococcus, and Lactobacillus.

  • Question 3: From the Krona plot shown from the Centrifuge results at the species level, what percentage of the sample is estimated to be Pseudomonas aeruginosa?

    Answer

    The Krona plot shows that Centrifuge estimates that 12% of the sample is Pseudomonas aeruginosa.

Assembly

NMDC EDGE Metagenome Assembly Tutorial Practice

Task: Log into NMDC EDGE and run the Metagenome Assembly workflow. Use the clean data output file from the project run in the ReadsQC Tutorial as the input. In this case, the file is interleaved paired data and only one file is required for input. When the run finishes, answer the questions below using the workflow outputs.

  • Question 1: How many contigs were generated from the assembly?

    Answer

    3,196 contigs were assembled.

  • Question 2: How many scaffolds were generated from the assembly?

    Answer

    3,141 scaffolds were created.

Annotation

NMDC EDGE Metagenome Annotation Tutorial Practice

Task: Log into NMDC EDGE and run the Metagenome Annotation workflow. Use the assembled contigs which are output from the project run in the Assembly Tutorial (assembled_contigs.fna). When the run finishes, answer the questions below using the workflow outputs.

  • Question 1: How many contigs had genes called sequences_with_genes?

    Answer

    3,031 contigs had genes called.

  • Question 2: Can you find coding sequences (genes) that were predicted by Prodigal? By GeneMark?

    Answer

    2,495 CDS (coding sequences or genes) were called by GeneMark and 936 CDS were called by Prodigal. Several should be seen in the output table.

  • Question 3: What is the coding density of this metagenome?

    Answer

    The coding density of the metagenome is 89.15%.

MAGs Generation

NMDC EDGE MAGs Generation Tutorial Practice

Task: Log into NMDC EDGE and run the Metagenome MAGs workflow. Use the assembled contigs and the read mapping file which are output from the project run in the Assembly Tutorial (assembled_contigs.fna and pairedMapped_sorted.bam) and the combined functional annotation file from the Annotation Tutorial (the file ending in functional_annotation.gff). When the run finishes, answer the questions below using the workflow outputs.

  • Question 1: Calculate the percentage of the contigs that were binned.

    Answer

    24% of the contigs were binned (binned contigs divided by total number of binned and unbinned contigs)

  • Question 2: How many bins were determined to be high quality (HQ)? How many bins were determined to be medium quality (MQ)?

    Answer

    One bin was determined to be high quality and five bins were determined to be medium quality.

  • Question 3: What is the organism that was identified from the bin that is most complete and has the least contamination (the highest quality bin)? (Note: Scroll to the far right of the summary table in the results to get the species assignment.)

    Answer

    The organism called by GTDBTK for the highest quality bin is Bacillus marinus.