# download compleasm and its dependencies (miniprot and hmmsearch)
wget https://github.com/huangnengCSU/compleasm/releases/download/v0.2.6/compleasm-0.2.6_x64-linux.tar.bz2
tar -jxvf compleasm-0.2.6_x64-linux.tar.bz2
# Install pandas if necessary
pip3 install pandas # or conda install pandas
# Run compleasm if lineage is known
compleasm_kit/compleasm.py download primates # download data to mb_download/
compleasm_kit/compleasm.py run -t16 -l primates -a hg38.fa -o hg38-mb # run the pipeline
# Automatically detect lineage (requiring sepp)
conda install -c bioconda sepp # if sepp hasn't been installed
compleasm_kit/compleasm.py run --autolineage -a hg38.fa -o hs38-mb - Getting Started
- Installation
- Running
- Main Modules
- Using
runsubmodule to evaluate genome completeness from genome assembly - Using
analyzesubmodule to evaluate genome completeness from provided miniprot alignment - Using
downloadsubmodule to download lineage - Using
miniprotsubmodule to run miniprot alignment - Using
listsubmodule to show local or remote Busco lineages - Using
proteinsubmodule to assess the completeness of input proteins - Output description
- Citing compleasm
Compleasm is developed on python3.
Compleasm can be installed with conda. If you don't have conda, please install miniconda or anaconda first. Then you can create a new environment with compleasm installed.
conda create -n <your_env_name> -c conda-forge -c bioconda compleasm
conda activate <your_env_name>
compleasm -h
Compleasm can be installed with docker. If you don't have docker, please install docker first. Then you can pull the docker image with compleasm installed.
VERSION=0.2.6
docker run huangnengcsu/compleasm:v${VERSION} compleasm -h
Compleasm can be installed with singularity. If you don't have singularity, please install singularity first. Then you can pull the singularity image with compleasm installed.
VERSION=0.2.6
singularity exec docker://huangnengcsu/compleasm:v${VERSION} compleasm -h
wget https://github.com/huangnengCSU/compleasm/releases/download/v0.2.6/compleasm-0.2.6_x64-linux.tar.bz2
tar -jxvf compleasm-0.2.6_x64-linux.tar.bz2
compleasm_kit/compleasm.py -h
git clone https://github.com/huangnengCSU/compleasm.git
You can run the compleasm.py script directly or copy it to other locations then run it.
git clone https://github.com/lh3/miniprot
cd miniprot && make
wget http://eddylab.org/software/hmmer/hmmer.tar.gz
tar zxf hmmer.tar.gz
cd hmmer-3.3.2
./configure --prefix /your/install/path
make
make check
make install
git clone https://github.com/smirarab/sepp.git
cd sepp
python setup.py config -c
python setup.py install
run Run compleasm including miniprot alignment and completeness evaluation
analyze Evaluate genome completeness from provided miniprot alignment
download Download specified BUSCO lineage
list List local or remote BUSCO lineages
miniprot Run miniprot alignment
This will download the specified lineage (or automatically search for the best lineage with autolineage mode), align the protein sequences in the lineage file to the genome sequence with miniprot, and parse the miniprot alignment result to evaluate genome completeness.
python compleasm.py run [-h] -a ASSEMBLY_PATH -o OUTPUT_DIR [-t THREADS]
[-l LINEAGE] [-L LIBRARY_PATH] [-m {lite,busco}] [--specified_contigs SPECIFIED_CONTIGS [SPECIFIED_CONTIGS ...]]
[--miniprot_execute_path MINIPROT_EXECUTE_PATH] [--hmmsearch_execute_path HMMSEARCH_EXECUTE_PATH]
[--autolineage] [--sepp_execute_path SEPP_EXECUTE_PATH]
[--min_diff MIN_DIFF] [--min_identity MIN_IDENTITY] [--min_length_percent MIN_LENGTH_PERCENT]
[--min_complete MIN_COMPLETE] [--min_rise MIN_RISE]
-a, --assembly_path Input genome file in FASTA format
-o, --output_dir The output folder
-t, --threads Number of threads to use
-l, --lineage Specify the name of the BUSCO lineage to be used. (e.g. eukaryota, primates, saccharomycetes etc.)
-L, --library_path Folder path to download lineages or already downloaded lineages.
If not specified, a folder named "mb_downloads" will be created on the current running path by default to store the downloaded lineage files.
-m, --mode The mode of evaluation. Default mode is busco.
lite: Without using hmmsearch to filtering protein alignment.
busco: Using hmmsearch on all candidate predicted proteins to purify the miniprot alignment to improve accuracy.
--specified_contigs Specify the contigs to be evaluated, e.g. chr1 chr2 chr3. If not specified, all contigs will be evaluated.
--outs output if score at least FLOAT*bestScore [0.95]
--miniprot_execute_path Path to miniprot executable file.
If not specified, compleasm will search for miniprot in the directory where compleasm.py is located, the current execution directory, and system environment variables.
--hmmsearch_execute_path Path to hmmsearch executable file.
If not specified, compleasm will search for hmmsearch in the directory where compleasm.py is located, the current execution directory, and system environment variables.
--autolineage Automatically search for the best matching lineage without specifying lineage file.
--sepp_execute_path Path to sepp executable file. This is required if you want to use the autolineage mode.
--min_diff The thresholds for the best matching and second best matching. default=0.2
--min_identity The identity threshold for valid mapping results. default=0.4
--min_length_percent The fraction of protein for valid mapping results. default=0.6
--min_complete The length threshold for complete gene. default=0.9
# with lineage specified
python compleasm.py run -a genome.fasta -o output_dir -l eukaryota -t 8
# autolineage mode
python compleasm.py run -a genome.fasta -o output_dir -t 8 --autolineage
# with custom specified already downloaded lineage folder
python compleasm.py run -a genome.fasta -o output_dir -l eukaryota -t 8 -L /path/to/lineages_folder
# specify contigs
python compleasm.py run -a genome.fasta -o output_dir -l eukaryota -t 8 --specified_contigs chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 chr20 chr21 chr22
This will directly parse the provided miniprot alignment result to evaluate genome completeness. The execute command of miniprot should be like miniprot --trans -u -I --outs=0.95 --gff -t 8 ref-file protein.faa > output.gff.
python compleasm.py analyze [-h] -g GFF -l LINEAGE -o OUTPUT_DIR [-t THREADS] [-L LIBRARY_PATH]
[-m {lite,busco}] [--hmmsearch_execute_path HMMSEARCH_EXECUTE_PATH]
[--specified_contigs SPECIFIED_CONTIGS [SPECIFIED_CONTIGS ...]]
[--min_diff MIN_DIFF] [--min_identity MIN_IDENTITY] [--min_length_percent MIN_LENGTH_PERCENT]
[--min_complete MIN_COMPLETE] [--min_rise MIN_RISE]
-g, --gff Miniprot output gff file
-l, --lineage BUSCO lineage name
-o, --output_dir Output analysis folder
-t, --threads Number of threads to use
-L, --library_path Folder path to stored lineages.
-m, --mode The mode of evaluation. Default mode is fast.
lite: Without using hmmsearch to filtering protein alignment.
busco: Using hmmsearch on all candidate predicted proteins to purify the miniprot alignment to improve accuracy.
--hmmsearch_execute_path Path to hmmsearch executable
If not specified, compleasm will search for hmmsearch in the directory where compleasm.py is located, the current execution directory, and system environment variables.
--specified_contigs Specify the contigs to be evaluated, e.g. chr1 chr2 chr3. If not specified, all contigs will be evaluated.
Threshold parameters are same as run module.
# analysis with miniprot output gff file
python compleasm.py analyze -g miniprot.gff -o output_dir -l eukaryota -t 8
# specify contigs
compleasm analyze -g miniprot.gff -o output_dir -l eukaryota -t 8 --specified_contigs chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 chr20 chr21 chr22
This will download the specified lineages and save to the specified folder.
python compleasm.py download [-h] [-L LIBRARY_PATH] lineages [lineages ...]
positional arguments:
lineages Specify the names of the BUSCO lineages to be downloaded. (e.g. eukaryota, primates, saccharomycetes etc.)
optional arguments:
-L, --library_path The destination folder to store the downloaded lineage files.
If not specified, a folder named "mb_downloads" will be created on the current running path by default.
python compleasm.py download saccharomycetes primates brassicales -L /path/to/lineages_folder
or
python compleasm.py download saccharomycetes,primates,brassicales -L /path/to/lineages_folder
This will run miniprot alignment and output the gff file.
python compleasm.py miniprot [-h] -a ASSEMBLY -p PROTEIN -o OUTDIR [-t THREADS] [--miniprot_execute_path MINIPROT_EXECUTE_PATH]
-a, --assembly Input genome file in FASTA format
-p, --protein Input protein file
-o, --outdir Miniprot alignment output directory
-t, --threads Number of threads to use
--outs output if score at least FLOAT*bestScore [0.95]
--miniprot_execute_path Path to miniprot executable file.
If not specified, compleasm will search for miniprot in the directory where compleasm.py is located, the current execution directory, and system environment variables.
python compleasm.py miniprot -a genome.fasta -p protein.faa -o output_dir -t 8
This will list the local or remote BUSCO lineages.
python compleasm.py list [-h] [--remote] [--local] [-L LIBRARY_PATH]
--remote List remote BUSCO lineages
--local List local BUSCO lineages
-L, --library_path Folder path to stored lineages.
# list local lineages
python compleasm.py list --local -L /path/to/lineages_folder
# list remote lineages
python compleasm.py list --remote
This will evaluate the completeness of input proteins.
python compleasm.py protein [-h] -p PROTEINS -l LINEAGE -o OUTDIR [-t THREADS]
[-L LIBRARY_PATH]
[--hmmsearch_execute_path HMMSEARCH_EXECUTE_PATH]
-p, --proteins Input protein file
-l, --lineage BUSCO lineage name
-o, --outdir Output analysis folder
-t, --threads Number of threads to use
-L, --library_path Folder path to stored lineages
--hmmsearch_execute_path Path to hmmsearch executable.
If not specified, compleasm will search for miniprot in the directory where compleasm.py is located, the current execution directory, and system environment variables.
python compleasm.py protein -p input.faa -l eukaryota -t 8 -o output_dir
The assessment result by compleasm is saved in the file summary.txt in the output folder. These BUSCO genes are categorized into the following classes:
- S (Single Copy Complete Genes): The BUSCO genes that can be entirely aligned in the assembly, with only one copy present.
- D (Duplicated Complete Genes): The BUSCO genes that can be completely aligned in the assembly, with more than one copy present.
- F (Fragmented Genes, subclass 1): The BUSCO genes which only a portion of the gene is present in the assembly, and the rest of the gene cannot be aligned.
- I (Fragmented Genes, subclass 2): The BUSCO genes in which a section of the gene aligns to one position in the assembly, while the remaining part aligns to another position.
- M (Missing Genes): The BUSCO genes with no alignment present in the assembly.
If you use compleasm, please cite:
Neng Huang, Heng Li, compleasm: a faster and more accurate reimplementation of BUSCO. Bioinformatics, 39, btad595, 2023. doi:10.1093/bioinformatics/btad595
