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:

The pipeline is executed per Batch and therefore the folder structure looks like following:

|-- multiqc
|-- pipeline_info
|-- references
`-- <batch>

Download and build references

Output files
└── <genome>
    ├── bowtie2
    │   ├── <genome>.1.bt2
    │   ├── <genome>.2.bt2
    │   ├── <genome>.3.bt2
    │   ├── <genome>.4.bt2
    │   ├── <genome>.rev.1.bt2
    │   └── <genome>.rev.2.bt2
    ├── <genome>.fa
    ├── <genome>.gtf
    ├── star
    │   ├── chrLength.txt
    │   ├── chrNameLength.txt
    │   ├── chrName.txt
    │   ├── chrStart.txt
    │   ├──
    │   ├──
    │   ├──
    │   ├── Genome
    │   ├── genomeParameters.txt
    │   ├── Log.out
    │   ├── SA
    │   ├── SAindex
    │   ├── sjdbInfo.txt
    │   ├──
    │   ├──
    │   └──
    └── versions.yml

The pipeline downloads references from GENCODE database. This is required, because the MARS-seq is using ERCC spike-ins, which have to be appended. Next it builds bowtie2 index. If --velocity flag is set, star index is also built.

Prepare pipeline

Output files
  • data/
    • amp_batches.txt: Amplification batches
    • gene_intervals.txt: Information about gene (chromosome, start, end, strand and symbol)
    • seq_batches.txt: Sequencing batches
    • wells_cells.txt: Well cells
    • *fastq.gz: Raw reads

At the beginning the pipeline validates the input *xlsx files which are further converted into .txt files. The majority of internal tools are written in Perl by the original authors. The nf-core/marsseq is trying to simplify these steps while replicating the necessary formats and executions in the background. Because the pipeline uses bowtie2 as a default aligner, reads are furher split into subfiles of 4,000,000 reads per file so the aligner doesn’t run out of memory.

Label reads

In this intermediate step, reads are further processed and barcodes (CB + UMI) is transferred from R2 to R1. This is important as the CB is further used in the demultiplexing step.

  • R1 structure: LA (3bp) + PB (4bp) + cDNA (66bp) + RA (2bp)
  • R2 structure: CB (7bp) + UMI (8bp)


  • LA: left adapter
  • PB: pool barcode
  • RA: right adapter
  • CB: cell barcode
  • UMI: Unique Molecular Indentifier

In this step, files are not saved in the overal results, they reside in the work folder.

Align reads

Split reads are aligned using bowtie2. Next, all the aligned reads are merged into one SAM file which is used as an input for demultiplexing.

If --velocity flag is set, the reads are also aligned using StarSolo to estimated both spliced and unspliced reads which can be used for RNA velocity estimation. This is an additional plugin which we developed. In short MARS-seq2.0 reads are converted to 10X v2 format. Additionally, a whitelist is generated for aligned to perform demultiplexing.

Output files
  • <batch>
    • <batch>.sam: Merged aligned reads into one SAM file with bowtie2
    • velocity/
      • Solo.out/*: Output from StarSolo (Gene, GeneFull, SJ, Velocyto and Barcode.stats)
      • Aligned.sortedByCoord.out.bam: Aligned reads
      • STAR alignment report containing the mapping results summary
      • Log.out and Log.progress.out: STAR log files containing detailed information about the run. Typically only useful for debugging purposes
      • <batch>.cutadapt.log: Log file from running cutadapt
      • <batch>_{1,2}.trim.fastq.gz: Trimmed pair-end converted 10X v2 reads
      • File containing filtered splice junctions detected after mapping the reads
      • whitelist.txt: File containing cell barcodes (combination of pool and cell barcode)


Output files
  • <batch>
    • output/
      • _debug: Debugging information
      • A directory that contains tables with the number of IVT products per each(well,gene) pair of all the processed amplification batches where each row is a gene and each column is a well/cell. The filename of a table corresponds to it’s amplification batch ([amplification batch ID].txt)
      • QC: Intermediate QC stats later used to generate QC_reports
      • A directory that contains tables with the number of molecules with a single IVT products per each(well,gene) pair of all the processed amplification batches where each row is a gene and each column is a well/cell. The filename of a table corresponds to it’s amplification batch (`[amplification batch ID].txt)
      • A directory that contains the expression tables of all the processed amplification batches. Each table contains he number of detected molecules for each (well,gene) pair where each row is a gene and each column is a well/cell. The filename of a table corresponds to it’s amplification batch ([amplification batch ID].txt)
      • amp_batches_stats.txt:
      • amp_batches_summary.txt:

Demultiplexing step where pipeline generates a count matrix for invidivual amplification batch. The count matrix can be found in <batch>/output/ The information above have been taken from original documentation for MARS-seq2.0 which can be round here.


QC report

Output files
  • <batch>
    • output/
      • QC_reports: For each sequencing batch a QC report is generated in [sequencing batch ID].pdf. Each contains a detailed QC reports for all the amplification batches associated with it.

Internal script for generating QC report after bowtie2 alignment and demultiplexing.


Output files
  • fastqc/
    • *_fastqc.html: FastQC report containing quality metrics.
    • * Zip archive containing the FastQC report, tab-delimited data file and plot images.

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.

MultiQC - FastQC sequence counts plot

MultiQC - FastQC mean quality scores plot

MultiQC - FastQC adapter content plot

NB: The FastQC plots displayed in the MultiQC report shows untrimmed reads. They may contain adapter sequence and potentially regions with low quality.


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

Workflow reporting and genomes

Pipeline information

Output files
  • pipeline_info/
    • Reports generated by Nextflow: execution_report.html, execution_timeline.html, execution_trace.txt and
    • 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.

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.