unknown 131 assembly, annotation and analysis
Anna McLoon, Caitlin Rigby, Francesca Gerbasi
Generated August 20, 2024


from biokbase.narrative.jobs.appmanager import AppManager
AppManager().run_app_batch(
    [{
        "app_id": "kb_uploadmethods/import_fastq_noninterleaved_as_reads_from_staging",
        "tag": "release",
        "version": "5b9346463df88a422ff5d4f4cba421679f63c73f",
        "params": [{
            "fastq_fwd_staging_file_name": "Unknown_131_S142_R1_001.fastq.gz",
            "fastq_rev_staging_file_name": "Unknown_131_S142_R2_001.fastq.gz",
            "name": "Unknown_131_paired_reads"
        }],
        "shared_params": {
            "sequencing_tech": "Illumina",
            "single_genome": 1,
            "read_orientation_outward": 0,
            "insert_size_std_dev": None,
            "insert_size_mean": None
        }
    }],
    cell_id="65a4fb35-1eb8-4267-b0e2-ef7a4afddc18",
    run_id="1d8de1df-7425-4e8d-86a3-933604442aa4"
)
Assess Read Quality with FastQC - v0.12.1
A quality control application for high throughput sequence data.
This app completed without errors in 2m 3s.
Report
Links
  • index.html - HTML files generated by fastqc that contains report on quality of reads
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/172258
  • Unknown_131_paired_reads_172258_37_1.fwd_fastqc.zip - Zip file generated by fastqc that contains original images seen in the report
  • Unknown_131_paired_reads_172258_37_1.rev_fastqc.zip - Zip file generated by fastqc that contains original images seen in the report
Trim Reads with Trimmomatic - v0.36
Trim paired- or single-end Illumina reads with Trimmomatic.
This app completed without errors in 4m 30s.
Objects
Created Object Name Type Description
Unknown_131_Paired_Reads_Trimmed_paired PairedEndLibrary Trimmed Reads
Unknown_131_Paired_Reads_Trimmed_unpaired_fwd SingleEndLibrary Trimmed Unpaired Forward Reads
Unknown_131_Paired_Reads_Trimmed_unpaired_rev SingleEndLibrary Trimmed Unpaired Reverse Reads
Report
Links
Assess Read Quality with FastQC - v0.12.1
A quality control application for high throughput sequence data.
This app completed without errors in 1m 46s.
Report
Links
  • index.html - HTML files generated by fastqc that contains report on quality of reads
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/172258
  • Unknown_131_Paired_Reads_Trimmed_paired_172258_40_1.rev_fastqc.zip - Zip file generated by fastqc that contains original images seen in the report
  • Unknown_131_Paired_Reads_Trimmed_paired_172258_40_1.fwd_fastqc.zip - Zip file generated by fastqc that contains original images seen in the report
Assemble Reads with IDBA-UD - v1.1.3
Assemble paired-end reads from single-cell or metagenomic sequencing technologies using the IDBA-UD assembler.
This app completed without errors in 7m 35s.
Objects
Created Object Name Type Description
Unknown_131_trimmed_IDBA.contigs Assembly Assembled contigs
Report
Summary
Assembly saved to: annamcloon:narrative_1709055269317/Unknown_131_trimmed_IDBA.contigs Assembled into 207 contigs. Avg Length: 25156.391304347828 bp. Contig Length Distribution (# of contigs -- min to max basepairs): 171 -- 505.0 to 43097.3 bp 17 -- 43097.3 to 85689.6 bp 11 -- 85689.6 to 128281.90000000001 bp 6 -- 128281.90000000001 to 170874.2 bp 1 -- 170874.2 to 213466.5 bp 0 -- 213466.5 to 256058.80000000002 bp 0 -- 256058.80000000002 to 298651.10000000003 bp 0 -- 298651.10000000003 to 341243.4 bp 0 -- 341243.4 to 383835.7 bp 1 -- 383835.7 to 426428.0 bp
Links
Assemble Reads with SPAdes - v3.15.3
Assemble reads using the SPAdes assembler.
This app completed without errors in 14m 4s.
Objects
Created Object Name Type Description
Unknown_131_trimmed_SPAdes.contigs Assembly Assembled contigs
Report
Summary
Assembly saved to: annamcloon:narrative_1709055269317/Unknown_131_trimmed_SPAdes.contigs Assembled into 100 contigs. Avg Length: 52162.94 bp. Contig Length Distribution (# of contigs -- min to max basepairs): 72 -- 532.0 to 51945.8 bp 13 -- 51945.8 to 103359.6 bp 4 -- 103359.6 to 154773.40000000002 bp 6 -- 154773.40000000002 to 206187.2 bp 0 -- 206187.2 to 257601.0 bp 3 -- 257601.0 to 309014.80000000005 bp 0 -- 309014.80000000005 to 360428.60000000003 bp 0 -- 360428.60000000003 to 411842.4 bp 0 -- 411842.4 to 463256.2 bp 2 -- 463256.2 to 514670.0 bp
Links
Classify Microbes with GTDB-Tk - v1.7.0
Obtain objective taxonomic assignments for bacterial and archaeal genomes based on the Genome Taxonomy Database (GTDB) ver R06-RS202
This app completed without errors in 34m 28s.
Report
Links
Build AssemblySet - v1.0.1
Allows users to create an AssemblySet object.
This app completed without errors in 11s.
Objects
Created Object Name Type Description
Unknown_131_Assembly_Set AssemblySet KButil_Build_AssemblySet
Summary
assembly objs in output set Unknown_131_Assembly_Set: 1
Annotate Genome/Assembly with RASTtk - v1.073
Annotate or re-annotate genome/assembly using RASTtk (Rapid Annotations using Subsystems Technology toolkit).
This app completed without errors in 4m 25s.
Objects
Created Object Name Type Description
Unknown_131_assembly_spades_rast.annotation Genome RAST re-annotated genome
Report
Summary
The RAST algorithm was applied to annotating a genome sequence comprised of 100 contigs containing 5216294 nucleotides. No initial gene calls were provided. Standard features were called using: glimmer3; prodigal. A scan was conducted for the following additional feature types: rRNA; tRNA; selenoproteins; pyrrolysoproteins; repeat regions; crispr. The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity. In addition to the remaining original 0 coding features and 0 non-coding features, 5778 new features were called, of which 228 are non-coding. Output genome has the following feature types: Coding gene 5550 Non-coding repeat 185 Non-coding rna 43 The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Links
  • genome_report.html - Feature function report for genome Unknown_131_assembly_spades_rast.annotation
Annotate Assembly and Re-annotate Genomes with Prokka - v1.14.5
Annotate Assembly and Re-annotate Genomes with Prokka annotation pipeline.
This app completed without errors in 2m 35s.
Objects
Created Object Name Type Description
Unknown_131_assembky_spades_Prokka.annotation Genome Annotated Genome
Summary
Annotated Genome saved to: annamcloon:narrative_1709055269317/Unknown_131_assembky_spades_Prokka.annotation Number of genes predicted: 5258 Number of protein coding genes: 5210 Number of genes with non-hypothetical function: 2856 Number of genes with EC-number: 1109 Number of genes with Seed Subsystem Ontology: 0 Average protein length: 266 aa.
Annotate and Distill Assemblies with DRAM
Annotate your assemblies, isolate genomes, or MAGs with DRAM and distill resulting annotations to create an interactive functional summary per genome or assembly. Use for KBase assembly objects.
This app completed without errors in 1h 12m 58s.
Objects
Created Object Name Type Description
Unknown_131_trimmed_SPAdes.contigs_DRAM Genome Annotated Genome
Unknown_131_DRAM GenomeSet DRAM annotation SPAdes
Report
Summary
Here are the results from your DRAM run.
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/172258
  • annotations.tsv - DRAM annotations in a tab separate table format
  • genes.fna - Genes as nucleotides predicted by DRAM with brief annotations
  • genes.faa - Genes as amino acids predicted by DRAM with brief annotations
  • genes.gff - GFF file of all DRAM annotations
  • rrnas.tsv - Tab separated table of rRNAs as detected by barrnap
  • trnas.tsv - Tab separated table of tRNAs as detected by tRNAscan-SE
  • genbank.tar.gz - Compressed folder of output genbank files
  • product.tsv - DRAM product in tabular format
  • metabolism_summary.xlsx - DRAM metabolism summary tables
  • genome_stats.tsv - DRAM genome statistics table
Build Metabolic Model
Construct a draft metabolic model based on an annotated genome.This app is now obsolete, replaced by the new ModelSEED2 app: MS2 - Build Prokaryotic Metabolic Models.
This app completed without errors in 1m 24s.
Objects
Created Object Name Type Description
Unknown_131_MR-1 FBAModel FBAModel-15 Unknown_131_MR-1
Unknown_131_MR-1.gf.1 FBA FBA-13 Unknown_131_MR-1.gf.1
Report
Summary
94026/Glc.O2.atp media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/172258

Released Apps

  1. Annotate and Distill Assemblies with DRAM
    • DRAM source code
    • DRAM documentation
    • DRAM Tutorial
    • DRAM publication
  2. Annotate Assembly and Re-annotate Genomes with Prokka - v1.14.5
    • Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30: 2068 2069. doi:10.1093/bioinformatics/btu153
  3. Annotate Genome/Assembly with RASTtk - v1.073
    • [1] Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. doi:10.1186/1471-2164-9-75
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, et al. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5. doi:10.1038/srep08365
    • [4] Kent WJ. BLAT The BLAST-Like Alignment Tool. Genome Res. 2002;12: 656 664. doi:10.1101/gr.229202
    • [5] Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25: 3389-3402. doi:10.1093/nar/25.17.3389
    • [6] Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25: 955 964.
    • [7] Cobucci-Ponzano B, Rossi M, Moracci M. Translational recoding in archaea. Extremophiles. 2012;16: 793 803. doi:10.1007/s00792-012-0482-8
    • [8] Meyer F, Overbeek R, Rodriguez A. FIGfams: yet another set of protein families. Nucleic Acids Res. 2009;37 6643-54. doi:10.1093/nar/gkp698.
    • [9] van Belkum A, Sluijuter M, de Groot R, Verbrugh H, Hermans PW. Novel BOX repeat PCR assay for high-resolution typing of Streptococcus pneumoniae strains. J Clin Microbiol. 1996;34: 1176 1179.
    • [10] Croucher NJ, Vernikos GS, Parkhill J, Bentley SD. Identification, variation and transcription of pneumococcal repeat sequences. BMC Genomics. 2011;12: 120. doi:10.1186/1471-2164-12-120
    • [11] Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11: 119. doi:10.1186/1471-2105-11-119
    • [12] Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics. 2007;23: 673 679. doi:10.1093/bioinformatics/btm009
    • [13] Akhter S, Aziz RK, Edwards RA. PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res. 2012;40: e126. doi:10.1093/nar/gks406
  4. Assemble Reads with IDBA-UD - v1.1.3
    • Peng Y, Leung HCM, Yiu SM, Chin FYL. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28: 1420 1428. doi:10.1093/bioinformatics/bts174
  5. Assemble Reads with SPAdes - v3.15.3
    • Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing. Journal of Computational Biology. 2012;19: 455-477. doi: 10.1089/cmb.2012.0021
    • Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using SPAdes De Novo Assembler. Curr Protoc Bioinformatics. 2020 Jun;70(1):e102. doi: 10.1002/cpbi.102.
  6. Assess Read Quality with FastQC - v0.12.1
    • FastQC source: Bioinformatics Group at the Babraham Institute, UK.
  7. Build AssemblySet - v1.0.1
    • Chivian D, Jungbluth SP, Dehal PS, Wood-Charlson EM, Canon RS, Allen BH, Clark MM, Gu T, Land ML, Price GA, Riehl WJ, Sneddon MW, Sutormin R, Zhang Q, Cottingham RW, Henry CS, Arkin AP. Metagenome-assembled genome extraction and analysis from microbiomes using KBase. Nat Protoc. 2023 Jan;18(1):208-238. doi: 10.1038/s41596-022-00747-x
    • Arkin AP, Cottingham RW, Henry CS, Harris NL, Stevens RL, Maslov S, et al. KBase: The United States Department of Energy Systems Biology Knowledgebase. Nature Biotechnology. 2018;36: 566. doi: 10.1038/nbt.4163
  8. Build Metabolic Model
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [4] Dreyfuss JM, Zucker JD, Hood HM, Ocasio LR, Sachs MS, Galagan JE. Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM. PLOS Computational Biology. 2013;9: e1003126. doi:10.1371/journal.pcbi.1003126
    • [5] Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5: 264 276.
  9. 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

Apps in Beta

  1. Classify Microbes with GTDB-Tk - v1.7.0
    • Pierre-Alain Chaumeil, Aaron J Mussig, Philip Hugenholtz, Donovan H Parks, GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database, Bioinformatics, Volume 36, Issue 6, 15 March 2020, Pages 1925 1927. DOI: https://doi.org/10.1093/bioinformatics/btz848
    • Parks, D., Chuvochina, M., Waite, D. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol 36, 996 1004 (2018). DOI: https://doi.org/10.1038/nbt.4229
    • Parks DH, Chuvochina M, Chaumeil PA, Rinke C, Mussig AJ, Hugenholtz P. A complete domain-to-species taxonomy for Bacteria and Archaea. Nat Biotechnol. 2020;10.1038/s41587-020-0501-8. DOI:10.1038/s41587-020-0501-8
    • Rinke C, Chuvochina M, Mussig AJ, Chaumeil PA, Dav n AA, Waite DW, Whitman WB, Parks DH, and Hugenholtz P. A standardized archaeal taxonomy for the Genome Taxonomy Database. Nat Microbiol. 2021 Jul;6(7):946-959. DOI:10.1038/s41564-021-00918-8
    • Matsen FA, Kodner RB, Armbrust EV. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics. 2010;11:538. Published 2010 Oct 30. doi:10.1186/1471-2105-11-538
    • Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9(1):5114. Published 2018 Nov 30. DOI:10.1038/s41467-018-07641-9
    • Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. Published 2010 Mar 8. DOI:10.1186/1471-2105-11-119
    • Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5(3):e9490. Published 2010 Mar 10. DOI:10.1371/journal.pone.0009490 link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835736/
    • Eddy SR. Accelerated Profile HMM Searches. PLoS Comput Biol. 2011;7(10):e1002195. DOI:10.1371/journal.pcbi.1002195