TeloComp
Telomere compliment tools
Install / Use
/learn @lxie-0709/TeloCompREADME
TeloComp
TeloComp is an efficient integrated software package for telomere extraction and complementation. It finalizes the output of the new genome and telomere complementation information and visualizes the complemented telomere portion through line graphs and covariance plots. It is more friendly to researchers and works towards a more complete T2T genome assembly.
<div align="center"> <img src="https://github.com/lxie-0709/TeloComp/blob/1.0.0/example/TeloComp.png" width="688px"> </div>Install
TeloComp is an executable program written in Python (3.11.6) that can be run directly by the user, but all dependencies of the program need to be installed before using TeloComp.
Dependencies
Please note that you must install the following versions of dependent software or higher before running:
The above software can be installed using conda, downloaded and installed from its github, or by running TeloComp's install.sh.
Building on Linux
To use the software, you need to follow the following steps to install it.
1.First, get the source code.
git clone git@github.com:lxie-0709/TeloComp.git
cd TeloComp
2.Next, execute install.sh and setup.sh in Dependencies and bin respectively “ to install the software dependencies and configure the software.
（1）Installing dependencies
$ sh install.sh
（2）Configuring TeloComp
$ sh setup.sh
3.Download GenomeSyn, add the GenomeSyn-1.2.7 file to your root directory, and perform the following steps：
$ chmod +x GenomeSyn-1.2.7
$ echo "export PATH=$PATH:/yourPATH/GenomeSyn-1.2.7/bin" >> ~/.bashrc
3.Finally, activate the environment variable and then verify that it is properly installed and executable with the following command:
# Activation environment
source ~/.bashrc
telocomp_Filter_1 -h
telocomp_Filter_2 -h
telocomp_Assembly -h
telocomp_maxmin -h
telocomp_Complement -h
telocomp_Collinearity -h
Usage
Note: TeloComp requires that you run the telomere complement command in the same directory from start to finish!
Filter
Options_1:
-h, --help show this help message and exit
--genome Input genome FASTA file.
--fai Input genome index (FAI) file.
--ont Input ONT data file (optional).
--hifi Input HiFi data file (optional).
--threads Number of threads to use with minimap2.
--motifs A list of telomeric repeat motifs to use for filtering (optional).
--max_break Maximum tolerable fracture length for soft shear.
--min_clip Minimum cutting length.
--Ob BAM output path after ONT filtering.
--Hb HiFi filtered BAM output path.
Options_2:
-h, --help show this help message and exit
--ont_bam Input ONT BAM
--hifi_bam Input HiFi BAM
-o, --out_dir Output directory
-c, --coverage The coverage parameter ranges from 0 to 100 and is used to trim reads
according to the selected coverage level
-p, --parallels Parameter for parallel processing of reads, with a default value of 5
--min_ratio The proportion of the original genome sequence to the length of the
reads, default=0.2
Run:
（1）Get the bam file containing the end software cutting sequence
telocomp_Filter_1 --genome /PATH/genome.fasta --fai /PATH/genome.fasta.fai --ont /PATH/ont.fastq.gz --hifi /PATH/hifi.fastq.gz --threads 50 --Ob /PATH/ont_out.bam --Hb /PATH/hifi_out.bam
（2）Detection, extraction, and processing of reads.Start by importing the bam file（Here, run the test using this procedure.）：
telocomp_Filter_2 --ont_bam /PATH/ont_out.bam --hifi_bam /PATH/hifi_out.bam -o PATH/output_dir/ -c 100 -p 10 --min_ratio 0.2
First, this step mainly detects and filters out reads containing telomeres outside the ends of the genome, trims the reads according to the coverage, and finally outputs the final results to the trim_L and trim_R directories according to the direction.
Assembly
Options:
-h, --help show this help message and exit
--dir_IN_L Directory containing left-aligned reads (FASTA format)
--dir_IN_R Directory containing right-aligned reads (FASTA format)
--flye Flye assembly module
-a, --assemble Alternative assemble module
-t , --threads Threads (default:20)
--min_overlap Min overlap (default:50)
--error_rate Error rate (default:0.15)
--kmer_size K-mer size (default:15)
-L , --lgsreads Long-read sequencing data
-W , --wgs1 Path to WGS reads (read 1)
-w , --wgs2 Path to WGS reads (read 2)
-N , --NextPolish Path to NextPolish tool
Run:
（1）Flye assembly module (default assembly)
telocomp_Assembly --dir_IN_L trim_L --dir_IN_R trim_R -L /PATH/test_HiFi.fq.gz -W /PATH/test_WGS_f1.fq.gz -w /PATH/test_WGS_r2.fq.gz -N /PATH/NextPolish -t 50
（2）assemble assembly module
telocomp_Assembly --dir_IN_L trim_L --dir_IN_R trim_R -L /PATH/test_HiFi.fq.gz -W /PATH/test_WGS_f1.fq.gz -w /PATH/test_WGS_r2.fq.gz -N /PATH/NextPolish -t 50 --assemble
Next,the screened and processed reads are assembled and polished, and the final results are output to the directory files_NP.
Extract the longest or shortest reads
If you choose to directly extract the longest or shortest reads, you can skip the assembly step and run this step directly.
Options:
-h, --help show this help message and exit
--Max_length Extract longest reads
--Min_length Extract shortest reads
--dir_ont Directory containing ONT files
--dir_hifi Directory containing HiFi files
-L , --lgsreads Long-read sequencing data
-W , --wgs1 Path to WGS reads (read 1)
-w , --wgs2 Path to WGS reads (read 2)
-N , --NextPolish Path to NextPolish tool
-t , --threads Number of threads to use (default: 20)
--polish Perform polishing with NextPolish
# Parameters of telocomp_Complement
--dir_Max Select the telomere reads obtained by polishing the longest reads to
add to the genome
--dir_Min Select the telomere reads obtained by polishing the shortest reads
to add to the genome
-m , --motif Telomeric repeats sequences, e.g., plant: CCCTAAA(TTTAGGG), animal:
TTAGGG(CCCTAA), etc.
-M , --motif_num Input the number of bases of the telomere motif
Run:
Extract reads
（1）Extract the longest reads
telocomp_maxmin --Max_length --dir_ont /PATH/algn_output_ont --dir_hifi /PATH/algn_output_hifi -L /PATH/test_HiFi.fq.gz -W /PATH/test_WGS_f1.fq.gz -w /PATH/test_WGS_r2.fq.gz -N /PATH/NextPolish -t 50 --polish
（2）Extract the shortest reads
telocomp_maxmin --Min_length --dir_ont /PATH/algn_output_ont --dir_hifi /PATH/algn_output_hifi -L /PATH/test_HiFi.fq.gz -W /PATH/test_WGS_f1.fq.gz -w /PATH/test_WGS_r2.fq.gz -N /PATH/NextPolish -t 50 --polish
（3）Without polishing, run the following code
telocomp_maxmin --Min_length --dir_ont /PATH/algn_output_ont --dir_hifi /PATH/algn_output_hifi
telocomp_maxmin --Max_length --dir_ont /PATH/algn_output_ont --dir_hifi /PATH/algn_output_hifi
Here you need to enter the untrimmed end alignment reads in the Filter, algn_output_ont and algn_output_hifi respectively, and finally output the polished reads to the directory MaxLength_NP and MinLength_NP.
（2）Telomere complement
telocomp_Complement --dir_Max -G /PATH/test_sequence.fasta -m CCCTAAA -M 7
telocomp_Complement --dir_Min -G /PATH/test_sequence.fasta -m CCCTAAA -M 7
This is the same as the Telomere complement below, both of which complete the telomere part to the original genome, but the running command is different.
Telomere complement
Option:
-G , --genome Input genome file (FASTA format)
--dir_contigs Input polished contigs
--dir_trim_L Input the trimmed reads. If the conditions are not
met, extract the shortest reads.
--dir_trim_R Input the trimmed reads. If the conditions are not
met, extract the shortest reads.
-L , --lgsreads Long-read sequencing data
-W , --wgs1 Path to WGS reads (read 1)
-w , --wgs2 Path to WGS reads (read 2)
-N , --NextPolish Path to NextPolish tool
-m , --motif Telomeric repeats sequences, e.g., plant:
CCCTAAA(TTTAGGG), animal: TTAGGG(CCCTAA), etc.
-M , --motif_num Input the number of bases of the telomere motif
--Normal Execute the command according to the general process
--dir_Max Select the telomere reads obtained by polishing the
longest reads to add to the genome
--dir_Min Select the telomere read
