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Pipeline description

Pipeline for bacterial assembly and annotation using nextflow.

Pipeline overview

  • FastQC v0.11.8 - read quality control.
  • Trimmomatic v.0.33 - adapter and low quality trimming.
  • Unicycler v.0.4.6 - prokaryote assembler.
  • Quast v4.1 - assemblies quality control
  • Kmerfinder v.3.1 - species and contamination determination.
  • PlasmidID v.1.4.1 - Assembly report and visualization.
  • ARIBA v.2.14.4 - Search resistance genes.

Note:

Depending on the analysis, we could have some ANALYSIS_IDs. This ANALYSIS_IDs are going to be composed of the date of the analysis, and an analysis identification. You can find a README in de ANALYSIS folder with a brief description of the different analysis.

Preprocessing

FastQC

FastQC gives general quality metrics about your reads. It provides information about the quality score distribution across your reads, the per base sequence content (%T/A/G/C). You get information about adapter contamination and other overrepresented sequences.

For further reading and documentation see the FastQC help.

Output directory: 03-assembly/fastqc

  • {sample_id}/{sample_id}_R[12]_fastqc.html
    • html report. This file can be opened in your favourite web browser (Firefox/chrome preferable) and it contains the different graphs that fastqc calculates for QC.
  • {sample_id}/{sample_id}_R[12]_fastqc
    • older with fastqc output in plain text.
  • {sample_id}/{sample_id}_R[12]_fastqc.zip
    • zip file containing the FastQC report, tab-delimited data file and plot images

Trimming

Trimmomatic (1) is used for removal of adapter contamination and trimming of low quality regions. Parameters included for trimming are:

  • Nucleotides with phred quality < 10 in 3'end.
  • Mean phred quality < 20 in a 4 nucleotide window.
  • Read lenght < 50

Results directory: 01-preprocessing

  • Files:
    • {sample_id}/{sample_id}_R[12]_filtered.fastq.gz: contains high quality reads with both forward and reverse tags surviving.
    • {sample_id}/{sample_id}_R[12]_unpaired.fastq.gz: contains high quality reads with only forward or reverse tags surviving.

Note:To see how your reads look after trimming, look at the FastQC reports in the 03-preprocQC directory

Kmerfinder

Kmerfinder (2) is a software used for species indentification and the determination of possible contamination in the sample. We use this software using the bacterial database provided by the developers, and with the "winner takes it all" algorithm. You can check here for a description of the columns in the output.

Output directory: 02-kmerfinder/{sample_id}/

  • data.json
    • results in json format.
  • results.spa
    • results in spa format.
  • results.txt
    • results in txt format. This is the format you have to use if you are going to open it with excel.

NOTE: You can also find in 99-stats a summary of all samples results (kmerfinder.csv).

Assembly

Unicycler

Unicycler (3) is an assembly pipeline for bacterial genomes. It can assemble Illumina-only read sets where it functions as a SPAdes-optimiser.

Output directory: 03-assembly/unicycler/{sample_id}

  • {sample_id}.fasta: fasta file containing the assembled reads in form of contigs and scaffolds. This is the file we use for annotation and upstream analysis.
  • {sample_id}.gfa: Graph files for the different assembly optimizations. This files can be used by advanced users with software like Bandage

QUAST

QUAST (5) evaluates genome assemblies. We compared the reference genome with the contigs and scaffold assemblies. The html results can be opened with any browser (we recommend using Google Chrome).

Output directory: 03-assembly/quast/quast_results

  • quast_results/results_{date}/report.html
    • Compressed format of the indexed variants file.
    • The meaning of the different metrics:
      • Contigs (≥ x bp): is total number of contigs of length ≥ x bp.
      • Total length (≥ x bp): is the total number of bases in contigs of length ≥ x bp.
      • Contigs: is the total number of contigs in the assembly.
      • Largest contig: is the length of the longest contig in the assembly.
      • Total length: is the total number of bases in the assembly.
      • Reference length: is the total number of bases in the reference genome.
      • GC (%): is the total number of G and C nucleotides in the assembly, divided by the total length of the assembly.
      • Reference GC (%): is the percentage of G and C nucleotides in the reference genome.
      • N50: is the length for which the collection of all contigs of that length or longer covers at least half an assembly.
      • NG50: is the length for which the collection of all contigs of that length or longer covers at least half the reference genome. This metric is computed only if the reference genome is provided.
      • N75 and NG75: are defined similarly to N50 but with 75 % instead of 50 %.
      • L50 (L75, LG50, LG75) is the number of contigs equal to or longer than N50 (N75, NG50, NG75). In other words, L50, for example, is the minimal number of contigs that cover half the assembly.

PlasmidID

PlasmidID was used to graphically represent the alignment of the reference genome relative to a given assembly. This helps to visualize the coverage of the reference genome in the assembly. To find more information about the output files refer to the documentation.

Output directory: 05-plasmidID/NO_GROUP/

  • 00_summary/FINAL_REPORT_NO_GROUP.tsv: .tsv table with the summary of the plasmids found in each sample and the times one plasmid appeared among all the samples.
  • {sample_id}/images/{sample_id}_{plasmid_id}.png: PNG file with the visualization of the alignment between the viral assembly and the reference viral genome.
  • {sample_id}/data/: Files used for drawing the circos images.
  • {sample_id}/database/: Annotation files used for drawing the circos images.
  • {sample_id}/fasta_files: Folder with fasta files that correspond to the selection of contigs/scaffolds required to reconstruct the reference genome generated in the images/ folder.
  • {sample_id}/log/: Log files.

ARIBA

ARIBA (6) was used to search for resistance genes and plasmids in different databases, for which it uses local assemblies.

Output directory: 06-ariba/

  • run/{sample_id}:
    • out.card1043-17run: Results of the Card database.
    • out.megares1043-17run: Results of the Megares database.
    • out.plasmidfinder1043-17run: Results of the plasmidfinder database.
    • out.srst2_argannot1043-17run: Results of the Arganot database.
    • out.vfdb_full1043-17run: Results of the VFDB database.
  • summary/:
    • out.summarycard.csv: Summary table of the Card database.
    • out.summarymegares.csv: Summary table of the Megares database.
    • out.summaryplasmidfinder.csv: Summary table of the plasmidfinder database.
    • out.summarysrst2_argannot.csv: Summary table of the Argannot database.
    • out.summaryvfdb_full.csv: Summary table of the VFDB database.

Bibliography

  1. Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible trimmer for Illumina Sequence Data. Bioinformatics, btu170.
  2. Rapid and precise alignment of raw reads against redundant databases with KMA Philip T.L.C. Clausen, Frank M. Aarestrup, Ole Lund.
  3. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017.
  4. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014 Jul 15;30(14):2068-9.
  5. Alexey Gurevich, Vladislav Saveliev, Nikolay Vyahhi and Glenn Tesler. QUAST: quality assessment tool for genome assemblies, Bioinformatics (2013) 29 (8): 1072-1075.
  6. Martin Hunt, Alison E. Mather, Leonor Sánchez-Bus, Andrew J. Page, Julian Parkhill, Jacqueline A Keane, Simon R. Harris. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom. 2017 Sep 4;3(10):e000131