Output

This document describes the output produced by the pipeline.

Pipeline overview

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

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.

NB: The FastQC plots displayed in the MultiQC report shows untrimmed reads. They may contain adapter sequence and potentially regions with low quality. To see how your reads look after trimming, look at the FastQC reports in the trim_galore directory.

Output directory: results/fastqc

  • sample_fastqc.html
    • FastQC report, containing quality metrics for your untrimmed raw fastq files
  • zips/sample_fastqc.zip
    • zip file containing the FastQC report, tab-delimited data file and plot images

Star-Fusion

Output directory: results/tools/StarFusion

  • star-fusion.fusion_predictions.tsv
    • contains all the predicted gene fusions
 ColumnDescription
JunctionReadCountIndicates the number of RNA-Seq fragments containing a read that aligns as a split read at the site of the putative fusion junction.
SpanningFragCountIndicates the number of RNA-Seq fragments that encompass the fusion junction such that one read of the pair aligns to a different gene than the other paired-end read of that fragment.
SpliceTypeIndicates whether the proposed breakpoint occurs at reference exon junctions as provided by the reference transcript structure annotations (ex. gencode).
LeftGene
LeftBreakpoint
RightGene
RightBreakpoint
LargeAnchorSupportcolumn indicates whether there are split reads that provide ‘long’ (set to length of 25 bases) alignments on both sides of the putative breakpoint.
FFPMfusion fragments per million total reads; Default: 0.1 (meaning at least 1 fusion-supporting rna-seq fragment per 10M total reads); TL;DR: can be adjusted by changing --min_FFPM
LeftBreakDinuc
LeftBreakEntropyRepresents Shannon entropy
RightBreakDinuc
RightBreakEntropyRepresents Shannon entropy
annotsAnnotation generated by FusionAnnotar

For more info check the documentation.

Fusioncatcher

Output directory: results/tools/Fusioncatcher

  • final-list_candidate-fusion-genes.txt
    • contains all the predicted gene fusions
 ColumnDescription
Gene_1_symbol(5end_fusion_partner)Gene symbol of the 5’ end fusion partner
Gene_2_symbol_2(3end_fusion_partner)Gene symbol of the 3’ end fusion partner
Gene_1_id(5end_fusion_partner)Ensembl gene id of the 5’ end fusion partner
Gene_2_id(3end_fusion_partner)Ensembl gene id of the 3’ end fusion partner
Exon_1_id(5end_fusion_partner)Ensembl exon id of the 5’ end fusion exon-exon junction
Exon_2_id(3end_fusion_partner)Ensembl exon id of the 3’ end fusion exon-exon junction
Fusion_point_for_gene_1(5end_fusion_partner)Chromosomal position of the 5’ end of fusion junction (chromosome:position
); 1-based coordinate
Fusion_point_for_gene_2(3end_fusion_partner)Chromosomal position of the 3’ end of fusion junction (chromosome:position
); 1-based coordinate
Spanning_pairsCount of pairs of reads supporting the fusion (including also the multimapping reads)
Spanning_unique_readsCount of unique reads (i.e. unique mapping positions) mapping on the fusion junction. Shortly, here are counted all the reads which map on fusion junction minus the PCR duplicated reads.
Longest_anchor_foundLongest anchor (hangover) found among the unique reads mapping on the fusion junction
Fusion_finding_methodAligning method used for mapping the reads and finding the fusion genes. Here are two methods used which are: (i) BOWTIE = only Bowtie aligner is used for mapping the reads on the genome and exon-exon fusion junctions, (ii) BOWTIE+BLAT = Bowtie aligner is used for mapping reads on the genome and BLAT is used for mapping reads for finding the fusion junction, (iii) BOWTIE+STAR = Bowtie aligner is used for mapping reads on the genome and STAR is used for mapping reads for finding the fusion junction, (iv) BOWTIE+BOWTIE2 = Bowtie aligner is used for mapping reads on the genome and Bowtie2 is used for mapping reads for finding the fusion junction.
Fusion_sequenceThe inferred fusion junction (the asterisk sign marks the junction point)
Fusion_descriptionType of the fusion gene (see the Table 2)
Counts_of_common_mapping_readsCount of reads mapping simultaneously on both genes which form the fusion gene. This is an indication how similar are the DNA/RNA sequences of the genes forming the fusion gene (i.e. what is their homology because highly homologous genes tend to appear show as candidate fusion genes). In case of completely different sequences of the genes involved in forming a fusion gene then here it is expected to have the value zero.
Predicted_effectPredicted effect of the candidate fusion gene using the annotation from Ensembl database. This is shown in format effect_gene_1/effect_gene_2, where the possible values for effect_gene_1 or effect_gene_2 are: intergenic, intronic, exonic(no-known-CDS), UTR, CDS(not-reliable-start-or-end), CDS(truncated), or CDS(complete). In case that the fusion junction for both genes is within their CDS (coding sequence) then only the values in-frame or out-of-frame will be shown.
Predicted_fused_transcriptsAll possible known fused transcripts in format ENSEMBL-TRANSCRIPT-1
/ENSEMBLE-TRANSCRIPT-B
, where are fused the sequence 1
of transcript ENSEMBL-TRANSCRIPT-1 with sequence POSITION-2
of transcript ENSEMBL-TRANSCRIPT-2
Predicted_fused_proteinsPredicted amino acid sequences of all possible fused proteins (separated by ”;”).

For more info check the documentation.

EricScript

Output directory: results/tools/Ericscript/tmp

  • fusions.results.filtered.tsv
    • contains all the predicted gene fusions
 ColumnDescription
GeneName1official gene name of 5’ gene.
GeneName2official gene name of 3’ gene.
chr1chromosome of 5’ gene.
Breakpoint1predicted breakpoint on 5’ gene.
strand1strand (-/+) of 5’ gene.
chr2chromosome of 3’ gene.
Breakpoint2predicted breakpoint on 3’ gene.
strand2strand (-/+) of 3’ gene.
EnsemblGene1Ensembl gene ID of 5’ gene.
EnsemblGene2Ensembl gene ID of 3’ gene.
crossingreadsthe number of paired end discordant reads.
spanningreadsthe number of paired end reads spanning the junction.
mean.insertsizemean of insert sizes of crossing + spanning reads.
homologyif filled, all the homologies between the fusion junction and Ensembl genes.
fusiontypeintra-chromosomal, inter-chromosomal, read-through or CIS.
InfoGene1gene information about 5’ gene.
InfoGene2gene information about 3’ gene.
JunctionSequencepredicted junction fusion sequence.
GeneExpr1Read count based estimation of the expression level of 5’ gene.
GeneExpr2Read count based estimation of the expression level of 3’ gene.
GeneExpr_fusedRead count based estimation of the expression level of the predicted chimeric transcript.
ESEdge score.
GJSGenuine Junction score.
USUniformity score.
EricScoreEricScore score (adaboost classifier).

For more info check the documentation.

Pizzly

Output directory: results/tools/Pizzly

  • pizzly_fusions.json
    • contains all the predicted gene fusions
 ColumnDescription
geneAid: reference id and name: gene name
geneBDescribes reference id and gene name
paircountNumber of paired count
splitcountNumber of split count
transcriptsList of all transcripts fasta_record, transcriptA, transcriptB, support, reads
readpairsList of read pairs containing (type, read1, read2)

For more info check the documentation.

Squid

Output directory: results/tools/Squid

  • fusions_annotated.txt
    • contains all the predicted gene fusions
 ColumnDescription
chr1chromosome name of the first breakpoint.
start1starting position of the segment of the first breakpoint, or the predicted breakpoint position if strand1 is ”-“
end1ending position of the segment of the first breakpoint, or the predicted breakpoint position if strand1 is ”+“
chr2chromosome name of the second breakpoint
start2starting position of the segment of the second breakpoint, or the predicted breakpoint position if strand2 is ”-“
end2ending position of the segment of the second breakpoint, or the predicted breakpoint position if strand2 is ”+“
nameTSV is not named yet, this column shows with dot.
scorenumber of reads supporting this TSV (without weighted by Discordant edge ratio multiplier)
strand1strand of the first segment in TSV.
strand2strand of the second segment in TSV.
num_concordantfrag_bp1number of concordant paired-end reads covering the first breakpoint. For a concordant paired-end read, it includes two ends and a inserted region in between, if any of the 3 regions covers the breakpoint, the read is counted in this number
num_concordantfrag_bp2number of concordant paired-end reads covering the second breakpoint. The count is defined in the same way as num_concordantfrag_bp1

For more info check the documentation.

Fusion Inspector

Output directory: results/tools/FusionInspector

  • finspector.fa
    • the candidate fusion-gene contigs (if you copy things elsewhere, make sure to also copy the index file: finspector.fa.fai)
  • finspector.bed
    • the reference gene structure annotations for fusion partners
  • finspector.junction_reads.bam
    • alignments of the breakpoint-junction supporting reads.
  • finspector.spanning_reads.bam
    • alignments of the breakpoint-spanning paired-end reads.

To visualize fusion genes in IGV tool first create a genome Menu->Genomes->Create .genome File, choose name and description, then choose the following files:

  • finspector.fa
    • make sure the index file finspector.fa.fai is in the same folder
  • finspector.gtf
    • use this for ‘Genes’
  • cytoBand.txt
    • use this for ‘optional Cytoband’

Add the bam files by choosing File->Load from File and make sure to select your generated mini genome in the upper-left corner. For more info and help check wiki page.

Summary report

Output directory: results/Report-<READS_BASE_NAME>

  • fusions.json
    • contains all main information about found fusions (fusion name, score, explanation of the score calculation, cherry picked output from fusion tools)
  • index.html
    • main dashboard containing the list of all detected fusions
  • *.html
    • each fusion gets a custom page with fetched data from the local database
  • fusions_list_filtered.txt
    • filtered list of found fusions (uses tool cutoff as filter, by default: 2, can be adjusted by adding -t <num> when running the tool)
  • fusions_list.txt
    • unfiltered list of found fusions

Tool detection

Graphs displaying ratio of fusion genes caught by different tools. The last part all tools is an intersection of all tools.

Tool detection

Found in database

Displays how many fusions were found in a downloaded databases of the summary report.

Known/unknown fusions

Tool detection distribution

For each fusion a sum of detected tools is calculated. This counts are then visualized in the graph below.

Known/unknown fusions

MultiQC

MultiQC is a visualisation 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 within the report data directory.

The pipeline has special steps which allow the software versions used to be reported in the MultiQC output for future traceability.

Output directory: results/multiqc

  • Project_multiqc_report.html
    • MultiQC report - a standalone HTML file that can be viewed in your web browser
  • Project_multiqc_data/
    • Directory containing parsed statistics from the different tools used in the pipeline

For more information about how to use MultiQC reports, see http://multiqc.info