Analyse microbial composition

Determine composition of organisms (typically microbial) in sequenced samples. Data analysis pipeline expect data from shotgun sequencing of a single target gene, for example 16S. Visually assess changes in compositions between several samples.

Purpose

  • Identify which organisms are present in sequenced samples
  • Compare an abundance of organisms with each other in a single sample
  • Compare abundances of organisms between samples

Required inputs

  • Sequenced reads in gzipped fastq format.
    • each sample is represented by two gzipped fastq files
    • standard output files of paired-end sequencing
  • .tax file with taxonomic description of each organism in reference fasta
    • TSV format
    • no header
    • each row represents a single target gene from the reference fasta
    • the first column represents the identifier of the gene (the first word after > symbol)
    • the second column represents taxonomy of the organism
    • for example
KF494428.1.1396 Bacteria;Epsilonbacteraeota;Campylobacteria;Campylobacterales;Thiovulaceae;Sulfuricurvum;Sulfuricurvum sp. EW1;;;;;;;;
AF506248.1.1375 Bacteria;Cyanobacteria;Oxyphotobacteria;Nostocales;Nostocaceae;Nostoc PCC-73102;Nostoc sp. 'Nephroma expallidum cyanobiont 23';;;;;;;;
EF603722.1.1487 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Muribaculaceae;;;;;;;;;;
...

|-- reads/original
        |-- <sample_1>_R1.fastq.gz
        |-- <sample_1>_R2.fastq.gz
        |-- <sample_2>_R1.fastq.gz
        |-- <sample_2>_R2.fastq.gz

In case, you are using Metaxa2 classifier, you also need reference genomes of target genes in fasta format.

|-- reference/<reference>
        |-- <reference>.fa
        |-- <reference>.tax

Generated outputs

  • Summary table with the number of reads per organism in sequenced sample
  • Pie plot with hierarchical taxonomical composition of the samples
  • Barplots for visual comparison of organisms abundance across sequenced samples

Example

Metaxa2 classifier

How to run example:

You need to provide reference sequences for this example to run. Sequences of the 16S gene (store them as reference/silva-16S/silva-16S.fa) may be downloaded from the Silva database. Sequences of the ITS gene (store them as reference/unite/unite.fa) may be downloaded from the Unite database.

cd /usr/local/snakelines/example/tatry

snakemake \
   --snakefile ../../snakelines.snake \
   --configfile config_metagenomics.yaml

Example configuration:

RDP classifier

How to run example:

RDP classifier has already prebuilt databases that may be used, specifically 16srrna, fungallsu, fungalits_warcup, fungalits_unite

cd /usr/local/snakelines/example/tatry

snakemake \
   --snakefile ../../snakelines.snake \
   --configfile config_metagenomics_rdp.yaml

Example configuration:

Planned improvements

  • Aggregate quality statistics of preprocess and mapping with the MultiQC
  • Add toy reference genome to example
  • Qiime2 based analysis