Forked from main branch for modification & independent use Evaluation and polishing workflows for T2T genome assemblies. Please cite if any of the codes shared in this repo was used:
Mc Cartney AM, Shafin K, Alonge M et al. Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies. Nat Methods (2022) doi: https://doi.org/10.1038/s41592-022-01440-3
For exact command lines and workflows used to generate the T2T-CHM13v1.0 and T2T-CHM13v1.1 assemblies, please refer to the Methods section in the CHM13-Issues repo. Note that some of the tools have been updated since then, and are tracked on this repo.
This README contains details about applying the automated polishing on general genome assemblies. Step by step detail is available in the automated_polshing folder.
The original script used in McCartney et al, 2021. In this version, the original script from McCartney et al. 2021 and subsequently Arang Rhie's manual edits has been further updated with a manually changed version of the Racon liftover chain.
- Winnowmap2
- Falconc available in pbipa package
- Racon (liftover branch)
- Meryl v1.3
- Merfin v1.0
- Samtools
- BCFtools
Allocate a fairly large amount of RAM relative to the size of your read set. The Racon step requires the loading of all reads into memory. For instance, a Revio flow cell (~100Gb) requires approximately 400Gb of RAM on a mammalian genome.
automated-polishing.sh <num_threads> <num_iterations> <in_draft_fasta> <in_reads> <in_readmers> <out_prefix> <read_type>
num_threads Number of threads to use.
num_iterations Number of polishing iterations to perform.
in_draft_fasta Path to the input FASTA/FASTQ containing draft sequences for polishing.
in_reads Path to the input reads file, in FASTA/FASTQ format. Can be gzipped.
in_readmers Path to a Meryl database of Illumina k-mers. Can be HiFi k-mers or true duplex k-mers, ONT simplex k-mers are not recommended (early 2024).
out_prefix Prefix of the output files. A folder will automatically be created if it does not exist.
read_type pb or ont. Optimize read alignments for PacBio HiFi reads (pb) or ONT reads (ont).
This script automatically launches Winnowmap2 to align a read set of choice, then uses falconc, a coordinate based version of Racon, and Merfin to call and filter polishing edits, and finalizes with bcftools to generate the polished consensus in one iteration. The number of iterations can be specified.
- Winnowmap2 will remap based on a new Meryl k-mer db in successive iterations.
A dedicated conda environment is highly recommended. A YML file is available in this repo. Otherwise, install each package independently (or load them on a SLURM-like cluster environment, etc). Note that using package managers for the installation of Racon will lead to a pipeline error with an error code of 'invalid option -L'. Racon must be installed from the following Git repo: https://github.com/pgrady1322/racon
Use these directions to build into a conda environment for the T2T Automated pipeline with the Conda YML in this Git repo.
conda env create -f t2tauto.yml -n t2t-auto-polisherConfirm that the modified version of Racon is installed by calling racon -h and checking for the -L flag in the options. If it is not, install manually via the steps below.
If you are performing a self install of all dependencies or already have them loaded on a HPC, the modified version of Racon must still be installed. All other dependencies can be from default repositories.
git clone --recursive https://github.com/pgrady1322/racon.git racon
cd racon
cmake -DCMAKE_BUILD_TYPE=Release ..
make