TelFusDetector provides functionalities for the detection of telomere fusions using whole-genome sequencing data.
If you use TelFusDetector (see License at the bottom of this page), please cite our publication Muyas & Gomez-Rodriguez et al. 2023.
TelFusDetector requires Python version >=3.7.0 and samtools.
- We strongly recommend building your own conda environment as follows:
conda create -n TelFusDetector -c bioconda python=3.7 samtools
conda activate TelFusDetector
- Additional dependencies can be installed by running the following commands:
pip install -r requirements.txt
This script detects telomere fusions in WGS DNA sequencing data sets (paired-end sequencing data). It can be run with multiple processes to speed up the computation.
python scripts/TelFusDetectorCaller.py --help
usage: TelFusDetectorCaller.py [-h] --bam BAM [--genome {Hg38,Hg19}]
[--bam2 BAM2] [--outfolder OUTFOLDER]
[--sample SAMPLE] [--tmpfolder TMPFOLDER]
[--threads THREADS]
TelFusDetector: This tool serves to detect telomere fusions in DNA sequencing
data sets (paired-end sequencing data)
optional arguments:
-h, --help show this help message and exit
--bam BAM BAM file to be analysed (Sorted by coordinate and
indexed)
--genome {Hg38,Hg19} Reference genome used for the alignment (Choose Hg38
or Hg19)
--bam2 BAM2 BAM file with unmapped reads (Sorted by coordinate and
indexed). If provided, it will speed up the
computation. If not provided, TelFusDetector will do
it internally.
--outfolder OUTFOLDER
Out directory
--sample SAMPLE Sample ID. All output files will start with this
string
--tmpfolder TMPFOLDER
Directory to save all temporary files. If it exits,
please empty it before running TelFusDetector
--threads THREADS Number of threads to use [Default: 1]
Out files generated
TelFusDetectorCaller.py will generate the next files:
- Sample.all_chromosomes.coverage.tsv : File listing the read length, total number of reads and mean coverage in the sample.
- Sample.summary_fusions.pass.tsv : File listing the PASS telomere fusion calls and all characteristics. It includes the read-pairs supporting the somatic telomere fusions and the read-pairs supporting the chromosome 9 endogenous fusion.
- Sample.summary_fusions.filtered.tsv : File listing the Filtered telomere fusion calls and the reason for being filtered.
This script calculates the telomere fusion (TF) rates per sample. For that, it takes the output generated by TelFusDetectorCaller.py (**.summary_fusions.pass.tsv*) and calculates telomere fusion rates. If available (and recommended), the user can provide the tumour purity to normalise the TF rates.
The tool permits flexibly calculating the TF rates by groups (orientation, breakpoint sequence...). Use the parameter --variables for that.
python scripts/TelFusDetectorRates.py --help
usage: TelFusDetectorRates.py [-h] --fusion_file FUSION_FILE
[--variables VARIABLES [VARIABLES ...]]
[--purity PURITY] [--outfile OUTFILE]
TelFusDetectorRate: Tool that takes the output generated by TelFusDetector to
calculate telomere fusion rates
optional arguments:
-h, --help show this help message and exit
--fusion_file FUSION_FILE
Telomere fusion summary file generated by
TelFusDetector (*summary_fusions.pass.tsv)
--variables VARIABLES [VARIABLES ...]
Input column names to be used for grouping the
telomere fusions (follow this format --variables VAR1
VAR2 VAR3 ...)
--purity PURITY Tumour purity [Default = 1]
--outfile OUTFILE Output file with the calculated telomere fusion rates
Out file generated
- File with the TF rates. If
--variablesprovided, TF rates for each group.
TelFusDetector is free for academic use only. If you are not a member of a public funded academic and/or education and/or research institution you must obtain a commercial license from EMBL Enterprise Management GmbH (EMBLEM); please email EMBLEM (info@embl-em.de).
If you have any comments or suggestions, please raise an issue or contact us:
- Francesc Muyas: fmuyas@ebi.ac.uk
- Isidro Cortes-Ciriano: icortes@ebi.ac.uk