Introduction Usage Parameters Output Releases

Introduction

This document describes the output produced by the pipeline. Most of the plots are taken from the MultiQC report, which summarises results at the end of the pipeline.

The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.

Pipeline overview

The pipeline is built using Nextflow and processes data using the following steps:

SAMtools faidx

SAMtools faidx is used to index the reference genome. The index file is required for downstream mapping steps.

Output files
  • samtools/faidx
    • <reference_genome>.fai: Index file for the reference genome
    • <reference_genome>.gzi: Gzip index file for the reference genome

FastQC or Falco

Output files
  • {fastqc,falco}/
    • {raw,preprocessed}
      • *html: FastQC or Falco report containing quality metrics in HTML format.
      • *.txt: FastQC or Falco report containing quality metrics in TXT format.
      • *.zip: Zip archive containing the FastQC report, tab-delimited data file and plot images (FastQC only).

FastQC gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the FastQC help pages.

If preprocessing is turned on, nf-core/bactmap runs FastQC/Falco twice -once before and once after adapter removal/read merging, to allow evaluation of the performance of these preprocessing steps. Note in the General Stats table, the columns of these two instances of FastQC/Falco are placed next to each other to make it easier to evaluate. However, the columns of the actual preprocessing steps (i.e, fastp, AdapterRemoval, and Porechop) will be displayed after the two FastQC/Falco columns, even if they were run ‘between’ the two FastQC/Falco jobs in the pipeline itself.

Info

Falco produces identical output to FastQC but in the falco/ directory.

fastq-scan

Output files
  • fastqscan/
    • raw/*.json: JSON formatted file of summary statistics for input fastq files.
    • processed/*.json: JSON formatted file of summary statistics for processed fastq files.
  • summaries/
    • raw_fastq-scan_summary.tsv: Final summary tsv file of sequencing statistics for analysis ready fastq files for all samples.
    • processed_fastq-scan_summary.tsv: Final summary tsv file of sequencing statistics for merged, subsampled fastq files for all samples.

fastq-scan is a tool for generating FASTQ summary statistics in JSON format.

fastp

fastp is a FASTQ pre-processing tool for quality control, trimmming of adapters, quality filtering and other features.

It is used in nf-core/bactmap for adapter trimming of short-reads.

Output files
  • fastp/
    • <sample_id>.fastp.fastq.gz: File with the trimmed unmerged fastq reads.
    • <sample_id>.merged.fastq.gz: File with the reads that were successfully merged.
    • <sample_id>.*{log,html,json}: Log files in different formats.

By default nf-core/bactmap will only provide the <sample_id>.fastp.fastq.gz file if fastp is selected. The file <sample_id>.merged.fastq.gz will be available in the output folder if you provide the argument --shortread_qc_mergepairs (optionally retaining un-merged pairs when in combination with --shortread_qc_includeunmerged).

You can change the default value for low complexity filtering by using the argument --shortread_complexityfilter_fastp_threshold.

AdapterRemoval

AdapterRemoval searches for and removes remnant adapter sequences from High-Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3’ end of reads following adapter removal. It is popular in the field of palaeogenomics. The output logs are stored in the results folder, and as a part of the MultiQC report.

Output files
  • adapterremoval/
    • <sample_id>.settings: AdapterRemoval log file containing general adapter removal, read trimming and merging statistics
    • <sample_id>.collapsed.fastq.gz - read-pairs that merged and did not undergo trimming (only when --shortread_qc_mergepairs supplied)
    • <sample_id>.collapsed.truncated.fastq.gz - read-pairs that merged underwent quality trimming (only when --shortread_qc_mergepairs supplied)
    • <sample_id>.pair1.truncated.fastq.gz - read 1 of pairs that underwent quality trimming
    • <sample_id>.pair2.truncated.fastq.gz - read 2 of pairs that underwent quality trimming (and could not merge if --shortread_qc_mergepairs supplied)
    • <sample_id>.singleton.truncated.fastq.gz - orphaned read pairs where one of the pair was discarded
    • <sample_id>.discard.fastq.gz - reads that were discarded due to length or quality filtering

By default nf-core/bactmap will only provide the .settings file if AdapterRemoval is selected.

You will only find the .fastq files in the results directory if you provide --save_preprocessed_reads. If this is selected, you may receive different combinations of .fastq files for each sample depending on the input types - e.g. whether you have merged or not, or if you’re supplying both single- and paired-end reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Warning

The resulting .fastq files may not always be the ‘final’ reads that go into subsampling, if you also run other steps such as run merging etc..

Porechop

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed and if a read has an adapter in its middle, it is considered a chimeric and it chopped into separate reads.

Output files
  • porechop/
    • <sample_id>.log: Log file containing trimming statistics
    • <sample_id>.fastq.gz: Adapter-trimmed file

The output logs are saved in the output folder and are part of MultiQC report.You do not normally need to check these manually.

You will only find the .fastq files in the results directory if you provide --save_preprocessed_reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Warning

We do not recommend using Porechop if you are already trimming the adapters with ONT’s basecaller Guppy.

Porechop_ABI

Porechop_ABI is an extension of Porechop. Unlike Porechop, Porechop_ABI does not use any external knowledge or database for the adapters. Adapters are discovered directly from the reads using approximate k-mers counting and assembly. Then these sequences can be used for trimming, using all standard Porechop options. The software is able to report a combination of distinct sequences if a mix of adapters is used. It can also be used to check whether a dataset has already been trimmed out or not, or to find leftover adapters in datasets that have been previously processed with Guppy.

Output files
  • porechop_abi/
    • <sample_id>.log: Log file containing trimming statistics
    • <sample_id>.fastq.gz: Adapter-trimmed file

The output logs are saved in the output folder and are part of MultiQC report.You do not normally need to check these manually.

You will only find the .fastq files in the results directory if you provide --save_preprocessed_reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Filtlong

Filtlong is a quality filtering tool for long reads. It can take a set of small reads and produce a smaller, better subset.

Output files
  • filtlong/
    • <sample_id>_filtered.fastq.gz: Quality or long read data filtered file
    • <sample_id>_filtered.log: log file containing summary statistics

You will only find the .fastq files in the results directory if you provide --save_preprocessed_reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Warning

We do not recommend using Filtlong if you are performing filtering of low quality reads with ONT’s basecaller Guppy.

Nanoq

nanoq is an ultra-fast quality filtering tool that also provides summary reports for nanopore reads.

Output files
  • nanoq/
    • <sample_id>_filtered.fastq.gz: Quality or long read data filtered file
    • <sample_id>_filtered.stats: Summary statistics report

You will only find the .fastq files in the results directory if you provide --save_preprocessed_reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Run Merging

nf-core/bactmap offers the option to merge FASTQ files of multiple sequencing runs or libraries that derive from the same sample, as specified in the input samplesheet.

This is the last possible preprocessing step, so if you have multiple runs or libraries (and run merging turned on), this will represent the final reads that will go into subsampling steps.

Output files
  • run_merging/
    • <sample_id>.fastq.gz: Concatenated FASTQ files on a per-sample basis

Note that you will only find samples that went through the run merging step in this directory. For samples that had a single run or library will not go through this step of the pipeline and thus will not be present in this directory.

This directory and its FASTQ files will only be present if you supply --save_runmerged_reads. Alternatively, if you wish only to have the ‘final’ reads that go into subsampling (i.e., that may have additional processing), do not specify this flag but rather specify --save_analysis_ready_fastqs, in which case the reads will be in the folder analysis_ready_reads.

Analysis Ready Reads

Info

This optional results directory will only be present in the pipeline results when supplying --save_analysis_ready_fastqs.

Output files
  • analysis_ready_fastqs/
    • <sample_id>_{fq,fastq}.gz: Final reads that underwent preprocessing and were sent for subsampling.

The results directory will contain the ‘final’ processed reads used as input for subsampling. It will only include the output of the last step of any combinations of preprocessing steps that may have been specified in the run configuration. For example, if you perform the read QC, the final reads that are sent to subsampling are the post-QC processed ones - those will be the ones present in this directory.

Warning

If you turn off all preprocessing steps, then no results will be present in this directory. This happens independently for short- and long-reads i.e. you will only have FASTQ files for short reads in this directory if you skip all long-read preprocessing.

Rasusa

The rasusa software is used to subsample reads to a depth cutoff of a default of 100 (unless the --subsampling_off flag is set)

Output files
  • rasusa/
    • <sample_id>.fastq.gz subsampled fastq files

read_stats

Output files
  • read_stats/
    • <sample_id>.tsv: Pre- and post-processing sequence statistics.
  • summaries
    • read_stats_summary.tsv: Final summary tsv file of pre- and post-processing sequence statistics for all samples.

Bowtie2

Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes.

It is used with nf-core/bactmap to map short reads to the reference genome.

Output files
  • bowtie2/
    • build/
      • *.bt2: Bowtie2 indices of reference genome
    • align/
      • <sample_id>.log: log file about the mapped reads
Info

While there is a dedicated section in the MultiQC HTML for Bowtie2, these values are not displayed by default in the General Stats table. Rather, alignment statistics to host genome is reported via samtools stats module in MultiQC report.

BWA MEM2

BWA MEM2 is a fast and accurate aligner for mapping short reads to reference sequences.

It is used with nf-core/bactmap to map short reads to the reference genome.

Output files
  • bwamem2/
    • index/
      • *.amb : BWA-MEM2 indices of reference genome
      • *.ann : BWA-MEM2 indices of reference genome
      • *.bwt : BWA-MEM2 indices of reference genome
      • *.pac : BWA-MEM2 indices of reference genome
      • *.sa : BWA-MEM2 indices of reference genome
Info

While there is a dedicated section in the MultiQC HTML for BWA-MEM2, these values are not displayed by default in the General Stats table. Rather, alignment statistics to host genome is reported via samtools stats module in MultiQC report.

minimap2

minimap2 is an alignment tool suited to mapping long reads to reference sequences.

It is used with nf-core/bactmap to map short reads to the reference genome.

Output files
  • minimap2/
    • build/
      • *.mmi2: minimap2 indices of reference genome.
Info

minimap2 is not yet supported as a module in MultiQC and therefore there is no dedicated section in the MultiQC HTML. Rather, alignment statistics to host genome is reported via samtools stats module in MultiQC report.

SAMtools sort

SAMtools sort is used to sort the BAM files generated by the mapping steps. The sorted BAM files are used for downstream variant calling.

Output files

  • samtools/sort/

    • <sample_id>.sorted.bam: Sorted BAM file containing reads that aligned against the user-supplied reference genome as well as unmapped reads
    • <sample_id>.sorted.bam.bai: Index file for the sorted BAM file

SAMtools stats

SAMtools stats collects statistics from a .sam, .bam, or .cram alignment file and outputs in a text format.

Output files
  • samtools/stats/
    • <sample_id>.sorted.bam.stats: File containing samtools stats output.
    • <sample_id>.sorted.bam.flagstat: Flagstat file for the sorted BAM file
    • <sample_id>.sorted.bam.idxstats: Index statistics file for the sorted BAM file

In most cases you do not need to check this file, as it is rendered in the MultiQC run report.

FreeBayes

FreeBayes is a haplotype-based variant detector designed to find SNPs, indels, and complex variants in short-read data. It is used with nf-core/bactmap to call variants from short-read data.

Output files
  • freebayes/
    • variants/
      • <sample_id>.vcf.gz: VCF file containing variants
      • <sample_id>.vcf.gz.tbi: Index file for the VCF file

Clair3

Clair3 is a variant caller for long-read data. It is used with nf-core/bactmap to call variants from long-read data.

Output files
  • clair3/
    • variants/
      • <sample_id>.vcf.gz: VCF file containing variants
      • <sample_id>.vcf.gz.tbi: Index file for the VCF file
      • <sample_id>.vcf.gz.stats: Statistics file for the VCF

BCFtools filter

The BCFtools software is used to call and filter variants found within the bam files.

Output files
  • variants/filtered
    • <sample_id>.vcf.gz filtered vcf files containing variants

BCFtools stats

BCFtools stats is used to generate statistics from the variant calling step. The output is a summary of the variants found in the vcf files.

Output files
  • bcftools/stats/
    • <sample_id>.stats BCFtools stats output files
    • <sample_id>.tsv BCFtools stats summary files

BCFtools consensus

The filtered vcf files are converted to a pseudogenome.

Output files
  • pseudogenomes/
    • <sample_id>.fas pseudogenome with a base at each position of the reference sequence

seqtk

The seqtk tool is used to identify the number of mapped bases within the pseudogenome fasta files.

Output files
  • seqtk/
    • <sample_id>.tsv tsv with base count and distribution for each pseudogenome
  • summaries
    • mapping_summary.tsv Summary of seqtk output for all samples

Align pseudogenomes

Only those pseudogenome fasta files that have a non-ACGT fraction less than the threshold specified will be included in the aligned_pseudogenomes.fas file. Those failing this will be reported in the low_quality_pseudogenomes.tsv file.

Output files
  • pseudogenomes/
    • aligned_pseudogenomes.fas alignment of all sample pseudogenomes and the reference sequence
    • low_quality_pseudogenomes.tsv a tab separated file of the samples that failed the non-ACGT base threshold

SNP-sites

Non-informative constant sites are removed from the alignment using snp-sites

Output files
  • snpsites/
    • constant.sites.txt A file with the number of constant sites for each base
    • filtered_alignment.fas Alignment with only informative positions (those positions that have at least one alternative variant base)

MultiQC

Output files
  • multiqc/
    • multiqc_report.html: a standalone HTML file that can be viewed in your web browser.
    • multiqc_data/: directory containing parsed statistics from the different tools used in the pipeline.
    • multiqc_plots/: directory containing static images from the report in various formats.

MultiQC is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.

Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see http://multiqc.info.

All tools in bactmap supported by MultiQC will have a dedicated section showing summary statistics of each tool based on information stored in log files.

You can expect in the MultiQC reports either sections and/or general stats columns for the following tools:

  • fastqc
  • fastp
  • adapterremoval
  • porechop
  • porechop_abi
  • filtlong
  • nanoq
  • samtools stats
  • bcftools stats
Info

The ‘General Stats’ table by default will only show statistics referring to pre-processing steps, and will not display statistics from mapping and variant calling, unless turned on by the user within the ‘Configure Columns’ menu or via a custom MultiQC config file (--multiqc_config).

Pipeline information

Output files
  • pipeline_info/
    • Reports generated by Nextflow: execution_report.html, execution_timeline.html, execution_trace.txt and pipeline_dag.dot/pipeline_dag.svg.
    • Reports generated by the pipeline: pipeline_report.html, pipeline_report.txt and software_versions.yml. The pipeline_report* files will only be present if the --email / --email_on_fail parameter’s are used when running the pipeline.
    • Reformatted samplesheet files used as input to the pipeline: samplesheet.valid.csv.
    • Parameters used by the pipeline run: params.json.

Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.
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