phasebook

Description

phasebook is a novel approach for reconstructing the haplotypes of diploid genomes from long reads de novo, that is without the need for a reference genome. This approach firstly groups the raw reads into small clusters of contiguous reads based on read overlaps. It then separates the reads within each cluster into two haplotypes in order to obtain local haplotype specific consensus sequences, referred to as super reads. Secondly, based on the haplotype-aware super reads computed, our approach constructs a haplotype aware super read overlap graph to extend super reads into haplotype aware contigs.

Installation and dependencies

Please note that phasebook is built for linux-based systems only. phasebook relies on the following dependencies:

• whatshap
• minimap2
• longshot
• samtools
• bcftools
• fpa
• overlap graph construction module from HaploConduct
• error correction modules from Racon, CONSENT, MECAT2 and NECAT
• g++ >=5.5.0 and with boost libraries
• python3

To install phasebook, firstly, it is recommended to intall the dependencies through Conda:

conda create -n phasebook python=3.7
conda activate phasebook
conda install -c bioconda whatshap=0.18 minimap2=2.18 longshot=0.4.1 samtools=1.12 bcftools=1.12 racon=1.4.20 fpa=0.5

Subsequently, pull down the code to the directory where you want to install, and compile the code:

git clone https://github.com/phasebook/phasebook.git
cd phasebook
sh install.sh

Running and options

The input read file is only required and the format should be FASTA or FASTQ. Other parameters are optional. Please run python phasebook.py -h to get details of optional parameters setting. The final polished haplotype aware contigs are included in the contigs.fa file under output directory.

Before running phasebook, please read through the following basic parameter settings, which may be helpful to obtain better assemblies. Note that the option -x indicates using preset parameters for assembly, which is recommended.

-i INFILE, --infile INFILE
                        input file in FASTA/FASTQ format (default: None)
-o OUTDIR, --outdir OUTDIR
                        output directory (default: .)
-t THREADS, --threads THREADS
                        number of threads (default: 1)
-p PLATFORM, --platform PLATFORM
                        sequencing platform(PacBio CLR/PacBio HiFi/Oxford
                        Nanopore): [pb/hifi/ont] (default: pb)
-x PRESET, --preset PRESET
                        use preset parameters
-g GENOMESIZE, --genomesize GENOMESIZE
                        genome size: small/large (default: small)
--overlaps OVERLAPS   input file in PAF format (default: None)
--min_cov MIN_COV     min coverage for trimming consensus (default: 4.0)
--min_identity MIN_IDENTITY
                        min identity for filtering overlaps (default: 0.75)
--min_read_len MIN_READ_LEN
                        min read length for processing (default: 1000)
--min_sread_len MIN_SREAD_LEN
                        min seed read length (default: 1000)
--min_ovlp_len MIN_OVLP_LEN
                        min overlap length for super reads construction
                        (default: 1000)
--n_correct N_CORRECT
                        times for self error correction of raw reads (default:
                        0)
--n_polish N_POLISH   times for super reads polishing (default: 2)
--sp_min_identity SP_MIN_IDENTITY
                        super reads min identity for filtering overlaps
                        (default: 0.98)
--min_cluster_size MIN_CLUSTER_SIZE
                        min size of read clusters (default: 4)
--trim_ends TRIM_ENDS
                        trim the erroneous bases in both ends, should be
                        either True or False (default: False)
--ctg_asm CTG_ASM    method to assemble super reads: [rb/naive], rb is time consuming, 
                        which is only recommended for small genomes (default: rb)
--correct_mode CORRECT_MODE
                        method to correct raw reads: [msa/hybrid], msa is much
                        faster than hybrid, which is recommended for large
                        genomes (default: msa)
--max_het_snps MAX_HET_SNPS
                        maximum number of heterozygous SNPs to determine the
                        contig overlap is from the identical haplotype or not
                        (default: 0)
--min_allele_cov MIN_ALLELE_COV
                        number of observations of each allele (default: 4)
--n_final_polish N_FINAL_POLISH
                        polish times for final contigs (default: 1)

Examples

One can test the program using the small PacBio HiFi reads file example/reads.fa. -g is used to set the running mode for small or large genomes. If set -g large, it will utilize more efficient approaches for read overlap calculation and filtering, as well as sequencing error correction, but may at the cost of assembly performance. In general,

For small genomes or genomic regions assembly (roughly, size < 50Mbp):

• PacBio HiFi reads

    cd example
    python ../scripts/phasebook.py -i reads.fa -t 8 -p hifi -g small -x 

• PacBio CLR reads

    python phasebook.py -i reads.fa -t 8 -p pb -g small -x 

• ONT reads

    python phasebook.py -i reads.fa -t 8 -p ont -g small -x 

For large genomes or genomic regions assembly:

• PacBio HiFi reads

    python phasebook.py -i reads.fa -t 8 -p hifi -g large -x 

• PacBio CLR reads

    python phasebook.py -i reads.fa -t 8 -p pb -g large -x 

• ONT reads

    python phasebook.py -i reads.fa -t 8 -p ont -g large -x 

One could also run phasebook on HPC when handling with very large genomes, such as human genome. Please see the shell script run_phasebook_on_hpc.sh for the details.

Possible issues during installation (optional)

• If g++ version of the system is not satisfied, one could try this to install:

conda install -c conda-forge gxx_linux-64=7.3.0
# replace the /path/to/ with your own path
ln -s /path/to/miniconda3/envs/phasebook/bin/x86_64-conda-cos6-linux-gnu-g++ /path/to/miniconda3/envs/phasebook/bin/g++
ln -s /path/to/miniconda3/envs/phasebook/bin/x86_64-conda-cos6-linux-gnu-gcc /path/to/miniconda3/envs/phasebook/bin/gcc

• If boost or zlib library is not installed, one could try this to install:

conda install -c conda-forge boost zlib
# set envionment variables
export LD_LIBRARY_PATH=/path/to/miniconda3/envs/phasebook/lib/:$LD_LIBRARY_PATH
export CPATH=/path/to/miniconda3/envs/phasebook/include/:$CPATH

• If compile error occurs something like /path/to/miniconda3/envs/phasebook/x86_64-conda_cos6-linux-gnu/bin/ld: cannot find -lboost_timer or cannot find -lz, which means it fails to link boost or zlib library, one could try this to solve:

ln -s /path/to/miniconda3/envs/phasebook/lib/libboost_* /path/to/miniconda3/envs/phasebook/x86_64-conda_cos6-linux-gnu/lib/
ln -s /path/to/miniconda3/envs/phasebook/lib/libz.* /path/to/miniconda3/envs/phasebook/x86_64-conda_cos6-linux-gnu/lib/
# then re-complile and install
sh install.sh

TODO

• Make pair-wise information be trackable in the final output. Currently, the output of phasebook is a bag of contigs from both haplotypes. For super-reads themselves, we do have kept the pair-wise information being tracked in the intermediate super-read file. But for the final output, we are working on this to make pair-wise information be trackable in the final assemblies as well.

Citation

Luo, X., Kang, X. & Schönhuth, A. phasebook: haplotype-aware de novo assembly of diploid genomes from long reads. Genome Biol 22, 299 (2021). Link