Fcirc

Fcirc is a pipeline for exploring linear transcripts and circRNAs of known fusions based on RNA-Seq data. Known fusion genes are from the multiple databases (COSMIC, ChimerDB, TicDB, FARE-CAFE and FusionCancer) or user-added gene-pairs. It costs less time to find fusions with higher sensitivity than existing methods for detecting fusions. The steps of Fcirc are as follows:

Fcirc pipeline

Installation

Fcirc is written in python3, requiring HISAT2 for aligning reads, samtools for selecting reads and python packages numpy, scipy, pysam.

Hardware requirements

For running Fcirc a computer with the following configuration is needed:

minimum 8 GB of RAM (aligning to human genome reference)
1 CPU (minimum)

Installing Fcirc from Github Clone

    git clone https://github.com/WangHYLab/fcirc

Installing required dependencies

hisat2 http://ccb.jhu.edu/software/hisat2/index.shtml
samtools http://www.htslib.org/download/
some python packages that can be installed by pip are as follows:
```
pip install -r requirements.txt
```
or
```
pip install numpy
pip install scipy
pip install pysam
pip install cutadapt
```
Make sure that hisat2 and samtools are added to environment variables so that Fcirc can invoke them.

Preparing genome resource and known fusion-pairs

The genome resource is hisat2 index, which can be downloaded from hisat2 website. For human fusion transcript detection, it's recommended to use genome_tran of GRCh38 or GRCh37. It can also be finished with FASTA sequence file and annotation GTF file by hisat2 script.
Known fusion-pairs can be downloaded from Github page and bipartite fusions index can be built by hisat2-build in reference_fusion_info directory as follows:

unzip fusion_total_index.zip
cd fusion_total_index
hisat2-build fusiongenes_ref_U.fa fusiongenes_ref_U
hisat2-build fusiongenes_ref_V.fa fusiongenes_ref_V

(optional) Add gene pairs of fusions in reference_fusion_info/fusion_table.tsv with 3 columns (gene-pairs, 5'gene, 3'gene) you are interested in. For human, genome FASTA file and annotation GTF file can be downloaded here.

python3 build_graph.py --genome absolute__to_genome --gtf absolute__to_gtf --tab absolute_path_to_fusionpairs_table
# e.g. python3 build_graph.py --genome ../ref/Homo_sapiens.GRCh38.dna.primary_assembly.fa --gtf ../ref/Homo_sapiens.GRCh38.105.gtf --tab reference_fusion_info/fusion_table.tsv  --outdir GRCh38_fusion_index

Warning: gene pairs joined with'--' not '-' should be placed in the first column of fusionpairs_table

Usage

Input data

The input data shall be single-end or paired-end RNA-Seq in FASTQ format, which can be raw data or trimmed data.

Command line options

Fcirc can be run with a simple command line.

python fcirc.py [options] -x <ht2-trans-idx> -f <ht2-fusion-idx-dir> -c <fusion-genes-coordinates> {-1 <fastq1> | -1 <fastq1> -2 <fastq2>}

Arguments can be used as following:

    Required:
        -x <ht2-trans-idx>, --trans_idx <ht2-trans-idx>
            transcription index filename prefix (minus trailing .X.ht2)
        -f <ht2-fusion-idx-dir>, --fusion_idx_dir <ht2-fusion-idx-dir>
            fusion index directory (contains fusiongenes_ref_U and fusiongenes_ref_V) 
        -1 <fastq1>, --file1 <fastq1>
            fastq file 1 (single-end pattern: only -1)
        -2 <fastq2>, --file2 <fastq2>
            fastq file 2 (paired-end pattern: -1 and -2, files should be like -1 xxx_1.fastq -2 xxx_2.fastq)

    Optional:
        -q <quality_val>
           the minimum phred qulaity of read(default:0)
        -c <fusion-genes-coordinates> --fusion_genes_coord
           fusion genes coordinates file (defalut: fusion_genes_coordinate.txt in fusion index directory)   
        -o <output_dir>, --output <outout_dir>
           output file directory (default: .)
        -t <int>, --thread <int>
           number of hisat2 alignment and pysam filter threads to launch (default: 1)    

    Others:
        -h, --help
            help information  
        -v, --version
            version information

Output data

The output includes:

fusion information
f-circRNA information

1. Fusion information is stored in a file 'fusion_results.tsv' as the following format:

#Fusion_Name    5'Gene  3'Gene  5'Gene_chr  5'Gene_strand   3'Gene_chr  3'Gene_strand   5'Gene_BreakPoint_Pos   3'Gene_BreakPoint_Pos   5'and3'_Common_Breakpoint_Seq   BreakpointReads_Count   BreakpointReads BreakpointStrand_Count(+,-) ScanningReads_Count ScanningReads   ScanningStrand_Count(+,-)   P-Value
PML--RARA   PML RARA    15  +   17  +   74023408    40348313    .   117 SRR3239817.48728782,SRR3239817.46047306,SRR3239817.46553524,SRR3239817.16929141,SRR3239817.19547854,SRR3239817.24567755,SRR3239817,......

The description of each column:
#Fusion Name - - The name of the fusion
5'Gene - - The gene encoding the 5' end of the fusion transcript
3'Gene - - The gene encoding the 3' end of the fusion transcript
5'Gene_chr- - The chromosome of 5'end gene
5'Gene_strand- - The strand of 5'end gene
3'Gene_chr -- The chromosome of 3'end gene
3'Gene_strand- - The strand of 3'end gene
5'Gene BreakPoint Pos - - The position of the breakpoint for the 5' end of the fusion transcript
3'Gene BreakPoint Pos - - The position of the breakpoint for the 3' end of the fusion transcript
5'and 3'Common Breakpoint Seq - - The same sequence at the breakpoint of the 3' end of the gene and the 5' end of the gene
BreakpointReads Count - -The number of reads spanning the fusion breakpoint
BreakpointReads - -The reads spanning the fusion breakpoint
BreakpointStrand Count(+,-) - - The number of reads located in forward strand and reverse strand respectively
ScanningReads Count(+,-) - - The number of pair of reads are located on both sides of the breakpoint
ScanningReads- - The reads located on both sides of the breakpoint
ScanningStrand_Count(+,-) -- The number of Scanning reads located in forward strand and reverse strand respectively
P-Value - - A p value indicating if reads around the breakpoint are evenly distributed

2. FcircRNA information is stored in a file 'fcircRNA_results.tsv' as the following format:

#FcircRNA_NO    Fusion Name Backsplice_start    Backsplice_end  Fusion5'_BreakPoint_Pos Fusion3'_BreakPoint_Pos Support_FcircRNA_Reads_Count    FcircRNA_Strand_Count(+, -) Support_FcircRNA_Reads
No_1    PML--RARA   15:74023268:+   17:40351924:+   15:74023408:+   17:40348313:+   1   0,1 SRR3239817.23906640
No_2    PML--RARA   15:73998438:+   17:40352058:+   15:74023408:+   17:40348313:+   3   0,3 SRR3239817.6429653,SRR3239817.3386413,SRR3239817.31829112
No_3    PML--RARA   15:73998328:+   17:40354455:+   15:74023408:+   17:40348313:+   1   0,1 SRR3239817.3123010
No_4    PML--RARA   15:73998193:+   17:40352044:+   15:74023408:+   17:40348313:+   5   0,5 SRR3239817.29876711,SRR3239817.36732283,SRR3239817.47058005,SRR3239817.32495621,SRR3239817.13611951
No_5    PML--RARA   15:73998454:+   17:40352406:+   15:74023408:+   17:40348313:+   1   0,1 SRR3239817.28808693
No_6    PML--RARA   15:74022909:+   17:40355327:+   15:74023408:+   17:40348313:+   3   0,3 SRR3239817.42010789,SRR3239817.11495312,SRR3239817.33451057
......
......
...

The description of each column:
#FcircRNA_NO - - The id of fusion circRNA
Fusion Name - - The name of fusion gene
Backsplice start - - The starting position of back-spliced end
Backsplice end - - The end position of back-spliced end
Fusion5'_BreakPoint_Pos - - The position of fusion breakpoint on 5'end
Fusion3'_BreakPoint_Pos - - The position of fusion breakpoint on 3'end
Support_FcircRNA_Reads_Count - - The number of reads supporting the f-circRNA
FcircRNA_Strand_Count(+, -) - - The number of reads supporting f-circRNA on positive and negative strand
Support FcircRNA Reads - - The reads supporting the f-circRNA

Quick start

You can start this pipeline using a testing RNA-Seq data, whose reads are partially from a RNA-Seq dataset SRR3239817 (NCBI SRA database), for an acute leukaemia cell line NB4.

python fcirc.py -t 4 -o fcirc_out -x transcriptome_HISAT2_index_path -f known_fusion_directory_path -c fusion_genes_coordinate.txt -1 test_fastq_path

It costs few minutes. If it runs successfully, some log information will be printed as following:

[2022-01-13 21:48:19] Start running # fcirc/fcirc.py -t 1 -o fcirc_test -x ref/grch38_tran/genome_tran -f fcirc/fusion_total_index/ -1 fcirc/test_data/test.fastq.gz
[2022-01-13 21:48:27] Finish mapping reads to transcription!
[2022-01-13 21:48:27] Finish mapping reads to fusion references U!
[2022-01-13 21:48:27] Finish mapping reads to fusion references V!
[2022-01-13 21:48:27] Finish dropping unmapped read in fusion references U and V!
Find 274 Reads in U! 274 Reads in V!
[2022-01-13 21:48:27] Finish filtering fusion-related reads in fusion references U and V!
[2022-01-13 21:48:29] Finish mapping reads to inferred fusion references!
Find 22 kind(s) of fcircRNAs!
[2022-01-13 21:48:29] Finish all!See the result in 'fcircRNA_results.tsv'!

Citation

Cai Z, Xue H, Xu Y, et al. Fcirc: A comprehensive pipeline for the exploration of fusion linear and circular RNAs. Gigascience. 2020;9(6):giaa054. doi: 10.1093/gigascience/giaa054

WangHYLab / fcirc

readme