metaDMG-cpp is a fast and efficient method for estimating mutation and damage rates in ancient DNA data, especially from ancient metagenomes. It relies on commonly used alignment file formats bam/sam/sam.gz and can calculate the degree of damage from read data mapped against a single as well as multiple genomes. It is especially relevant for data where data have been mapped against multiple reference genomes or to speed up analysis for damage estimation for a single genome.
There are three possible modes for running metaDMG. In all cases, the program utilises the MD:Z field of the aux part of reads and is therefore reference-free.
Basic single genome analysis with one overall global estimate. Similar to the mapdamage2.0 programme (./metaDMG-cpp getdamage --run_mode 0).
Basic metagenomes (e.g. multiple genome alignments) analyses. Output is a damage estimate per reference, taxonomic name or accession no that includes all alignments without an LCA analysis (./metaDMG-cpp getdamage --run_mode 1).
Integrating a Least Common Ancestor algorithm (ngsLCA) which allows retrieving damage estimates for alignments classified to the given taxonomic levels (./metaDMG-cpp lca).
For all analyses, the output is a binary '.bdamage.gz' file, which contains a substitution matrix that can be accessed and read with the (./metaDMG print)' functionality.
metaDMG-cpp
requires HTSlib
, a common library used for handling high-throughput sequencing data, eigen3
and gsl
.
On Ubuntu these can be installed with:
sudo apt install libgsl-dev libeigen3-dev
To install metaDMG-cpp do:
git clone https://github.com/metaDMG-dev/metaDMG-cpp.git
cd metaDMG-cpp
make HTTSRC=../htslib
git submodule update --init --recursive
cd htslib
make
For installing latest updates:
make clean
git pull https://github.com/metaDMG-dev/metaDMG-cpp.git
conda create -c bioconda -n metaDMG metadmg
conda activate metaDMG
./metaDMG-cpp lca counts substitutions between read and reference on internal nodes within a taxonomy (e.g. species, genus and family level). To traverse up a taxonomic tree the program needs three files in NCBI taxonomy format. These can either be a custom taxonomy built as the NCBI taxonomy or simply rely on the NCBI taxonomy, or it can be a combination. NOTE the taxonomy file shall reflect the version of the database you are using.
Downloading resource files for the program from NCBI
mkdir ncbi_tax_dmp;
cd ncbi_tax_dmp/;
wget https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/new_taxdump/new_taxdump.zip;
unzip new_taxdump.zip;
wget https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/accession2taxid/nucl_gb.accession2taxid.gz;
gunzip nucl_gb.accession2taxid.gz;
Calculations of substitution matrices (without any LCA analysis), either at a:
./metaDMG-cpp getdamage [options] <in.bam>|<in.sam>|<in.cram>
Options: -n/--threads number of threads used for reading/writing (default: 4) -f/--fasta reference genome (required with CRAM) -l/--min_length reads shorter than minlength will be discarded (default: 35) -p/--print_length number of positions along the read termini that are used to estimate the damage (default: 5) -r/--run_mode 0: global (default) 1: local damage patterns will be calculated for each chr/scaffold contig. -i/--ignore_errors continue analyses even if there are errors -o/--out_prefix output prefix (default: meta)
# LCA analyses
Calculations, where each read, is classified to a given taxonomic level (based on the similarity of the alignments as specified below, we recommend --sim_score_low 0.95 --sim_score_high 1.0).
./metaDMG-cpp lca [options]
Options:
--threads number of threads used for reading/writing (default: 4)
--bam input alignment file SAM/SAM.gz/BAM
--names names.dmp.gz
--nodes nodes.dmp.gz
--acc2tax accesion to taxid table
--edit_dist_min minimum read edit distance
--edit_dist_max maximum read edit distance
--min_mapq minimum mapping quality
--min_length minimum read length
--sim_score_low number between 0-1
--sim_score_high number between 0-1
--fix_ncbi
--discard
--how_many integer for number of positions OBS rasmus will change this to --print_length
--lca_rank such as family/genus/species
--used_reads
--no_rank2species
--skip_no_rank
--weight_type
-i/--ignore_errors continue analyses even if there are errors 1 or stop when error 0 (default)
--temp temp prefix
-o/--out_prefix output prefix
# metaDMG print
`./metaDMG-cpp print file.bdamage.gz [-names file.gz -bam file.bam -ctga -countout] infile: (null) inbam: (null) names: (null) search: -1 ctga: 0 `
All options found below:
./metaDMG-cpp print
Usage: ./metaDMG-cpp print
Example ./metaDMG-cpp print file.bdamage.gz -names names.dmp.gz ./metaDMG-cpp print file.bdamage.gz -r 9639 -ctga ./metaDMG-cpp print file.bdamage.gz -countout Options: -ctga ONLY print CT+ and GA- (the damage ones) -countout print mismatch as counts and not as transition probabilites -r taxid Only print for specific taxid -names NCBI names.dmp.gz file - option to print taxonomic names instead of NCBI TaxID -bam print referencenames (Accession No.) from bamfile, otherwise it prints NCBI TaxId.
# metaDMG merge
`./metaDMG-cpp merge file.lca file.bdamage.gz `
All options found below:
./metaDMG-cpp merge
Usage: ./metaDMG-cpp merge file.lca file.bdamage.gz [-names names.dmp.gz -bam
Example Options: -howmany #integer for many positions. -nodes #needs taxonomic paths to calculate damage higher than species level /ncbi_tax_dump_files/nodes.dmp.gz -names #NCBI names.dmp file - option that prints taxonomic names to output
# metaDMG dfit
Performing numerical optimization of the deamination frequencies based on the mismatch matrix (.bdamage.gz) to estimate four parameters: A,q,c,phi. Either applying a beta-binomial distribution or binomial distribution as the choice for likelihood model.
A: Amplitude of damage on position one.
q: Relative decrease of damage per position.
c: Background noise, equivalent to sequencing errors.
phi: signifies the uncertainty of beta-binomial model, with larger values indicating the probability of deamination is reduced to binomial distribution.
The optimization can be performed in three modes, all of which depends on the input parameters and information stored within the .bdamage.gz file,
global: with one damage estimate for entire BAM file.
local: damage estimate for all chromosomes/contigs/scaffolds present in BAM header.
lca: damage estimates of the nodes within the lca tree structure.
`./metaDMG-cpp dfit file.bdamage.gz `
A simple help page is printed with
`./metaDMG-cpp dfit -h `
While an extended and full helppage is printed with --help and shown below.
-> ./metaDMG-cpp dfit --help
Extended helppage damage estimation using numerical optimization Estimates damage in either local, global or lca mode depending on the bdamage input format Dfit command performs either optimization of beta-binomial (default --nbootstrap = 0) or binomial model (--nbootstrap > 2)
Local mode: damage estimated for each reference/chromosome in the BAM file Global mode: one damage estimate for whole BAM file lca mode: damage estimated over the lca tree at different ranks
--help Print extended help page to see all options.
./metaDMG-cpp dfit file.bdamage.gz --names file.gz --nodes trestructure.gz --bam file.bam --showfits int --nopt int --nbootstrap int --seed int --doCI int --CI float --lib <ds,ss> --out file
------------ Required ------------- ./metaDMG-cpp dfit file.bdamage.gz bdamage file contains the misincorporation matrix, in global mode from getdamage command or local mode from lca command
------------ Optional -------------
--names #NCBI names.dmp file - option that prints taxonomic names to output
--nodes #needs taxonomic paths to calculate damage higher than species level
--bam In local mode - convert the internal id numbering from bdamage.gz to the reference in the bam header
--out Prefix for output name
--nopt Number of optimization calls (default: 10).
--seed Seed value for random number generators (default: computer time).
--rand Type of random number generator <0,1,2,3> 0: drand48_r, default for linux or unix, not available for MacOS 1: std::uniform_int_distribution 2: rand_r 3: erand48, default for MacOS.
--threads: Number of threads, default = 1, i.e. no threading
--lib double stranded (ds) use C>T (forward) and G>A (reverse); single stranded (ss) use C>T for both forward and reverse (default ds)
--nbootstrap number of bootstrap iterations. default: 1 -> use Beta-binomial model, -nbootstrap >1 use Binomial model
---- Optimization model specific ----
------ Beta-binomial model ------
--showfits: Verbose parameter, stored in the .dfit.txt.gz, default = 0, see documentation for full description of columns --showfits 0 [id;A;q;c;phi;llh;ncall;sigmaD;Zfit] id:contig; A:amplitute of damage; q:decrease in damage; c:offset (background noise); phi:variance between Beta-binomial and binomial model llh:minimized negative log-likelihood; ncall:optimization calls; sigmaD: standard deviation; Zfit: significance score
--showfits 1 [id;A;q;c;phi;llh;ncall;sigmaD;Zfit;
fwdxi;fwdxConfi;..;fwdxn;fwdxConfn..;
bwdx;dxConfn;..;bwdxn;bwdxConfn]
fwdx: damage estimates forward strand; fwdxConf: confidence interval; fbwdx: reverse strand; bwdxConfn: confidence interval.
i position 1 to position n (zero-index)
--showfits 2 [id;A;q;c;phi;llh;ncall;sigmaD;Zfit;
fwKi;fwNi;fwdxi;fwf0;fwdxConfi;..;fwKi;fwNi;fwdxi;fwfi;fwdxConfi..;
bwKi;bwNi;bwdxi;bwfi;bwdxConfi;..;bwKn;bwNn;bwdxn;fwfn;bwdxConfn]
fwKi: Number of transitions forward strand (C>T); fwNi: Number reference counts forward strand (C); fwfi: C>T frequency based on forward strand from bdamage file
bwKi: Number of transitions reverse strand (G>A); bwNi: Number reference counts reverse strand (G); bwfi: C>T frequency based on reverse strand from bdamage file
---------- Binomial model ----------
--showfits: Verbose parameter, stored in the .dfit.txt.gz, default = 0 --showfits 0 [id;A;q;c;phi;llh;ncall;sigmaD;Zfit;A_b;q_b;c_b;phi_b;A_CI_l;A_CI_h;q_CI_l;q_CI_h;c_CI_l;c_CI_h;phi_CI_l;phi_CI_h] id;A;q;c;phi;llh;ncall;sigmaD;Zfit estimates from beta-binomial (see above) A_b;q_b;c_b;phi_b;A_CI_l;A_CI_h;q_CI_l;q_CI_h;c_CI_l;c_CI_h;phi_CI_l;phi_CI_h estimates binomial model with bootstrap method (_b), confidence interval (_CI_l) and (*_CI_h)
--showfits 1 similar columns added as described above, using the bootstrap estimated parameters;
--showfits 2 similar columns added as described above, using the bootstrap estimated parameters;
--nbootstrap: Number of bootstrap iterations, default = 0 --doboot: Store all bootstrap iterations of [id,A_b,q_b,c_b,phi_b] in seperate file, suffix: .bdamage.gz.boot.stat.txt.gz --sigtype Determines the bootstrap method <1,2,3>, default = 1 0: Sample with replacement from the C>T frequency from the .bdamage format 1: Sample with replacement from the K and N column from the .bdamage format and calculates f column 1: Sample with replacement from binomial distribution defined from K and N column from the .bdamage format --CI: Desired confidence interval, default = 0.95 --doCI: Confidence interval type <0,1> 0: Mean and Standard Deviation-Based CI Calculation 1: Percentile CI Calculation
---------- Examples ---------- Local mode binomial: ./metaDMG-cpp getdamage Pitch6.bam -l 10 -p 15 -r 1 -o Pitch6getDMG ./metaDMG-cpp dfit Pitch6getDMG.bdamage.gz --showfits 1 Global mode binomial: ./metaDMG-cpp getdamage Pitch6.bam -l 10 -p 15 -r 0 -o Pitch6getDMG ./metaDMG-cpp dfit Pitch6getDMG.bdamage.gz --nbootstrap 2 --showfits 2 Lca mode beta-binomial: ./metaDMG-cpp lca --names names.dmp --nodes nodes.dmp --acc2tax acc2taxid.map.gz --weight_type 1 --fix_ncbi 0 --bam Pitch6.bam --out Pitch6lcatest ./metaDMG-cpp dfit Pitch6lcatest.bdamage.gz --names names.dmp --nodes nodes.dmp --showfits 0
# metaDMG aggregate
Aggregating the lca statistics when transversing through the tree structure, creating files with prefix .aggregate.stat.txt.gz
`./metaDMG-cpp aggregate file.bdamage.gz --lcastat lca.stat --names names.dmp --nodes nodes.dmp --out file --dfit `
-> ./metaDMG-cpp aggregate -h
Aggregation of lca produced statistics (mean length, variance length, mean GC, variance GC) when transversing up the nodes of the tree structure
./metaDMG-cpp aggregate file.bdamage.gz --names file.gz --nodes trestructure.gz --lcastat file.stat --out filename
--help Print extended help page to see all options. --names names.dmp.gz --nodes nodes.dmp.gz --lca lcaout.stat lca produced statistics --out Suffix of output name with the predetermined prefix (.aggregate.stat.txt.gz)