Generated August 18, 2020

Welcome to KBase's Narrative Interface!

What's a Narrative? Narratives are shareable, reproducible workflows that can include data, analysis steps, results, visualizations and commentary. Learn more...

Take the Tour: Choose "Narrative Tour" from the "Help" menu above. The tour walks you through the user interface, pointing out various useful aspects of it.

Get Some Data: Click the Add Data button in the Data Panel to search KBase data or upload your own. Mouse over a data object to add it to your Narrative. Learn more...

Analyze It: Use the Apps panel or the App Catalog to browse available analysis apps. Select an app to add it to your Narrative, fill in the fields, and click the "play" button to launch the app. Learn more...

Save and Share Your Narrative: Be sure to save your Narrative frequently. To let collaborators view your analysis steps and results, click the Share button. Or make your Narrative public and help expand the social web that KBase is building to make systems biology research more open, reproducible and collaborative. Learn more...

Find Documentation: For more information, please see the Narrative Interface User Guide or the tutorials.

Questions? Bug reports? Contact us!

Ready to begin adding to your Narrative? You can keep this Welcome cell or delete it by selecting "Delete cell" from the "..." menu in the top right corner of this cell.

from biokbase.narrative.jobs.jobmanager import JobManager
JobManager().get_job('5936df80e4b0b89082da638a')
Out[1]:
A quality control application for high throughput sequence data.
This app completed without errors in 4m 8s.
Trim paired- or single-end Illumina reads with Trimmomatic.
This app completed without errors in 11m 39s.
Objects
Created Object Name Type Description
ANG59-genome-trimmed-reads_paired PairedEndLibrary Trimmed Reads
ANG59-genome-trimmed-reads_unpaired_fwd SingleEndLibrary Trimmed Unpaired Forward Reads
ANG59-genome-trimmed-reads_unpaired_rev SingleEndLibrary Trimmed Unpaired Reverse Reads
Report
A quality control application for high throughput sequence data.
This app is still in progress.
No output found.
Assemble paired-end microbial reads using the A5 assembly pipeline.
This app completed without errors in 59m 46s.
Objects
Created Object Name Type Description
ANG59-genome-a5.contigs Assembly Assembled contigs
Summary
============= Raw Contigs ============ QUAST: All statistics are based on contigs of size >= 500 bp, unless otherwise noted (e.g., "# contigs (>= 0 bp)" and "Total length (>= 0 bp)" include all contigs). Assembly a5_contigs # contigs (>= 0 bp) 108 # contigs (>= 1000 bp) 99 Total length (>= 0 bp) 5331509 Total length (>= 1000 bp) 5325293 # contigs 108 Largest contig 411530 Total length 5331509 GC (%) 62.90 N50 121837 N75 53833 L50 13 L75 30 # N's per 100 kbp 2.89 ========== Filtered Contigs ========== ContigSet saved to: asuria25:narrative_1496767788159/ANG59-genome-a5.contigs Assembled into 108 contigs. Average Length: 49365.8240741 bp. Contig Length Distribution (# of contigs -- min to max basepairs): 72 -- 530.0 to 41630.0 bp 17 -- 41630.0 to 82730.0 bp 7 -- 82730.0 to 123830.0 bp 3 -- 123830.0 to 164930.0 bp 5 -- 164930.0 to 206030.0 bp 1 -- 206030.0 to 247130.0 bp 1 -- 247130.0 to 288230.0 bp 0 -- 288230.0 to 329330.0 bp 0 -- 329330.0 to 370430.0 bp 2 -- 370430.0 to 411530.0 bp
Output from Assemble with A5
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/21819
Assemble short microbial reads using the Velvet assembler.
This app completed without errors in 2m 20s.
Objects
Created Object Name Type Description
ANG59-genome-velvet.contigs Assembly Assembled contigs
Summary
============= Raw Contigs ============ QUAST: All statistics are based on contigs of size >= 500 bp, unless otherwise noted (e.g., "# contigs (>= 0 bp)" and "Total length (>= 0 bp)" include all contigs). Assembly velvet_contigs # contigs (>= 0 bp) 471 # contigs (>= 1000 bp) 268 Total length (>= 0 bp) 4720767 Total length (>= 1000 bp) 4659141 # contigs 310 Largest contig 155612 Total length 4689194 GC (%) 62.75 N50 52329 N75 21687 L50 29 L75 65 # N's per 100 kbp 248.53 ========== Filtered Contigs ========== ContigSet saved to: asuria25:narrative_1496767788159/ANG59-genome-velvet.contigs Assembled into 347 contigs. Average Length: 13554.6743516 bp. Contig Length Distribution (# of contigs -- min to max basepairs): 268 -- 302.0 to 15833.0 bp 32 -- 15833.0 to 31364.0 bp 16 -- 31364.0 to 46895.0 bp 9 -- 46895.0 to 62426.0 bp 10 -- 62426.0 to 77957.0 bp 5 -- 77957.0 to 93488.0 bp 2 -- 93488.0 to 109019.0 bp 1 -- 109019.0 to 124550.0 bp 1 -- 124550.0 to 140081.0 bp 3 -- 140081.0 to 155612.0 bp
Output from Assemble with Velvet
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/21819
Run QUAST (QUality ASsessment Tool) on a set of Assemblies to assess their quality.
This app is still in progress.
No output found.
Align sequencing reads to long reference prokaryotic genome sequences using Bowtie2
This app completed without errors in 9m 47s.
No output found.
Runs the CheckM lineage workflow to assess the genome quality of isolates, single cells, or genome bins from metagenome assemblies through comparison to an existing database of genomes.
This app produced errors.
No output found.

Apps

  1. Align Reads using Bowtie2 - v2.3.2
    • Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9: 357 359. doi:10.1038/nmeth.1923
    • Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10: R25. doi:10.1186/gb-2009-10-3-r25
  2. Assemble with A5
    • Coil, D., Jospin, G. and Darling, A.E., (2014). A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data. Bioinformatics, p.btu661.
  3. Assemble with Velvet
    • Zerbino, D. R., Birney, E. (2008) Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Research, 18(5), 821-829, doi: 10.1101/gr.074492.107
  4. Assess Genome Quality with CheckM - v1.0.18
    • Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25: 1043 1055. doi:10.1101/gr.186072.114
    • CheckM source:
    • Additional info:
  5. Assess Quality of Assemblies with QUAST - v4.4
    • [1] Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29: 1072 1075. doi:10.1093/bioinformatics/btt086
    • [2] Mikheenko A, Valin G, Prjibelski A, Saveliev V, Gurevich A. Icarus: visualizer for de novo assembly evaluation. Bioinformatics. 2016;32: 3321 3323. doi:10.1093/bioinformatics/btw379
  6. Assess Read Quality with FastQC - v0.11.5
    • FastQC source: Bioinformatics Group at the Babraham Institute, UK.
  7. Trim Reads with Trimmomatic - v0.36
    • Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30: 2114 2120. doi:10.1093/bioinformatics/btu170