Last update: Feb 27, 2025, Contributors: Minh Bui, Piyumalanthony, Rob Lanfear
Phylogenetic Dating
Bayesian dating with MCMCtree
From IQ-TREE 2.5 onwards, we provide the functionality in IQ-TREE to infer time trees using Bayesian MCMCtree method.
If you use this feature, please cite:
P. Demotte, M. Panchaksaram, N. Ly-Trong, M. dos Reis and B.Q. Minh (2025) IQ2MC: A New Framework to Infer Phylogenetic Time Trees Using IQ-TREE and MCMCtree.
IQ2MC workflow for time tree inference
The IQ2MC workflow has three steps that integrate IQ-TREE and MCMCtree. The final output is a time-estimated phylogeny starting from a multiple-sequence alignment as displayed in the following figure.
Step1: Given an input multiple sequence alignment, IQ-TREE will infer the maximum likelihood tree using the IQ-TREE tree search algorithm. Note that, the tree estimated here should be a rooted tree or you need to manually root the tree as MCMCtree only accepts rooted trees for phylogenetic dating. In this step, IQ-TREE also estimates the best-fitted substitution model for the data if you do not specify the model. This step is optional if you provide a rooted tree, the MSA, and the substitution model for step 2.step2: For fast approximate likelihood dating, MCMC requires the gradients and the Hessian/Hessians of the branch lengths calculated at maximum likelihood estimates. Given the rooted tree with fossil/tip calibrations, the substitution model, and the MSA, IQ-TREE generates the Hessian file containing the gradients and the Hessian/Hessian and all required files to run MCMCtree for dating.step3: Now, you can directly run MCMCtree from the IQ-TREE output of step 2 and infer the time tree.
Estimating the gradients and the Hessian for MCMCtree dating
To obtain the Hessian file for MCMCtree approximate likelihood dating, you need to perform step 2 in the workflow. For this step, IQ-TREE expects a rooted tree file, the substitution model, and the multiple sequence alignment. When --dating mcmctree option is used as below, IQ-TREE performs the gradients and the Hessian calculation and generates the Hessian file. This Hessian file is compatible with MCMCtree and you can use it as an input to MCMCtree for approximate likelihood dating.
If the alignment file is called example.phy and the rooted tree file is called example_tree.nwk,
iqtree -s example.phy -m GTR+G4 -te example_tree.nwk --dating mcmctree --prefix example
Note that, Here we generate the Hessian file for a fixed rooted tree. You can directly input the rooted tree which already contains fossil/tip calibration information added using tree editing tools such as FigTree. When using the above command, IQ-TREE generates the following files which can be used to run MCMCtree for phylogenetic dating.
example.mcmctree.hessian: the hessian file which contains the gradients vector and the Hessian for approximate likelihood dating.example.rooted.nwk: the rooted tree file which is compatible with the Hessian file. It is necessary to use this tree file with MCMCtree for dating as the Hessian is calculated with respect to the ordering of taxa of this tree file.example.mcmctree.ctl: the control file that can be used directly to run MCMCtree from IQ-TREE output of step 2.example.dummy.aln: It is not necessary to use the alignment with MCMCtree under approximate likelihood dating. However, in the current format MCMCtree requires an alignment, and you can simply use this dummy alignment file as the input to MCMCtree to save compute.
You can specify more parameters in the workflow to generate the control file accurately for the analysis with IQ-TREE.
iqtree -s example.phy -m GTR+G4 -te example_tree.nwk --dating mcmctree --mcmc-iter 20000,200,50000 --mcmc-bds 1,1,0.5 --mcmc-clock IND
--mcmc-iter burnin,samplefreq,nsample: use to set number of burin samples, sample frequency and number of MCMC samples in the control file. In the above example, burnin =20000, samplefreq = 200 and nsample = 50000--mcmc-bds birth-rate,death-rate,sampling-fraction: use to set the parameters for birth-death prior in MCMCtree. In the above example, birth-rate=1, death-rate=1 and sampling-fraction=0.5--mcmc-clock <EQUAL|IND|CORR>: use to set clock model for MCMCtree. Currently supported clocks models are EQUAL: global clock with equal rates, IND: independent rates model with independent rates across lineages and CORR: correlated clock model with auto-correlated rates across the lineages.
Using partitions and Mixture models for approximate likelihood dating
IQ-TREE supports three partition models for approximate likelihood dating. Under the Edge-unlinked (EUL) model, IQ-TREE generates the Hessian file which contains separate gradients and Hessian for each partition. For the Edge-linked (EL) partition model, the Hessian file contains only one gradient vector and a Hessian as branches are shared across partitions.
Since IQ-TREE supports RAxML and NEXUS style partitions input file, you can use partitions defined in the following format.
DNA, part1 = 1-100 DNA, part2 = 101-450
If your partition file is called example.nex,
iqtree -s example.phy -Q example.nex -m GTR+G4 -te example_tree.nwk --dating mcmctree
Here, IQ-TREE generates the Hessian file using the GTR+G4 model for all partitions. If you need to use different models for each partition, you need to create a more flexible NEXUS file like the following.
#nexus
begin sets;
charset part1 = 1-100;
charset part2 = 101-450;
charpartition mine = GTR+G4:part1, HKY:part2;
end;
Here, IQ-TREE uses GTR+G4 model for partition 1, and HKY model for partition 2 respectively. Using -q and -p options, you can generate the Hessian file which considers edge-linked equal branch partition models and edge-linked proportional branch length models respectively.
IQ-TREE also supports mixture models for the Hessian file generation. You can simply specify DNA or Amino Acid Mixture model as following,
iqtree -s example.phy -m "MIX{GTR,HKY}+G4" -te example_tree.nwk –-dating mcmctree
If you need to use an Amino Acid profile mixture model such as C60 model,
iqtree -s example.phy -m LG+G4+C60 -te example_tree.nwk –-dating mcmctree
If you are using ModelFinder or MixtureFinder, you need to follow a two-step approach. First, you can estimate the best-fit model for the data using ModelFinder or MixtureFinder. Then, the Hessian file can be generated using --dating mcmctree option using the estimated models.
How to run MCMCtree
You can directly run MCMCtree from the control file generated by IQ-TREE in step
- The command to run MCMCtree with the control file is,
mcmctree example.mcmctree.ctl
The control file generated by IQ-TREE has the following format. You can simply edit the control file as necessary. For an example you may need to increase burin and sample frequency for MCMC convergence.
seed = -1 * The computer’s current time is used when seed < 0. seqfile = example.dummy.phy * A dummy alignment only allow to run MCMCtree treefile = example.rooted.nwk * Rooted newick tree with annotated fossil/tip dates mcmcfile = example.mcmctree.log * MCMC log of parameters that can be examined in Tracer outfile = example.mcmctree.out * Output of the summarized results of MCMCtree ckpfile = example..mcmctree.ckp * Checkpoint file of MCMCtree hessianfile = example.mcmctree.hessian * File with gradient and hessian matrix checkpoint = 1 * 0: nothing; 1 : save; 2: resume ndata = 1 * number of partitions seqtype = 0 * 0 : nucleotides; 1: codons; 2: AAs (not required if the approximate likelihood method is used) usedata = 2 * 0: sampling from priors with no data; 1: exact slow likelihood; 2: approximate likelihood clock = 2 * 1: global clock with equal rates; 2: independent rates; 3: correlated rates RootAge = <1.0 * safe constraint on root age, used if no fossil for root in the rooted tree file. BDparas = 1,1,0.5 * birth-rate, death rate, sampling priors for sampling times finetune = 1: 0.1 0.1 0.1 0.01 .5 * auto (0 or 1) : times, musigma2, rates, mixing, paras, FossilErr print = 1 * 1: normal output; 2: verbose output *** These parameters are used for multi-loci partitioned data (ndata > 1), see dos Reis et al.(2013) rgene_gamma = 2 2 * alpha and beta parameter of Dirichlet-gamma prior for mean rate across loci for clock=2 or 3 sigma2_gamma = 1 10 * alpha and beta parameter of Dirichlet-gamma prior for rate variance across loci for clock=2 or 3 *** These parameters control the MCMC run burnin = 20000 sampfreq = 200 nsample = 50000 *** Note: Total number of MCMC iterations will be burnin + (sampfreq * nsample) *** The following parameters only needed to run MCMCtree with exact likelihood (usedata = 1) *** no need to change anything for approximate likelihood (usedata = 2) model = 0 * 0:JC69, 1:K80, 2:F81, 3:F84, 4:HKY85 alpha = 0 * 0: No rate heterogeneity across sites; otherwise: fixed alpha parameter of the Gamma distribution ncatG = 0 * Number of rate categories for the discrete Gamma distribution cleandata = 0 * remove sites with ambiguity data (1:yes, 0:no)? kappa_gamma = 6 2 * gamma prior for kappa of the HKY model alpha_gamma = 1 1 * alpha and beta parameter of Gamma distribution for heterogeneous rates across sites
Note that, if you generate the hessain file from IQ-TREE, it is necessary to use the rooted tree file generated by IQ-TREE to be used in MCMCtree. The ckpfile and hessianfile options are new and only work for the PAML release in IQ-TREE (https://github.com/iqtree/paml). If you use another MCMCtree version/release, you can simply remove those options from control file and rename the hessian file to in.BV to run MCMCtree without any errors.
Least Square Dating (LSD2)
Since IQ-TREE 2.0.3, we integrate the least square dating (LSD2) method to build a time tree when you have date information for tips or ancestral nodes. So if you use this feature please cite:
Thu-Hien To, Matthieu Jung, Samantha Lycett, Olivier Gascuel (2016) Fast dating using least-squares criteria and algorithms. Syst. Biol. 65:82-97. https://doi.org/10.1093/sysbio/syv068
We will now walk through examples but the full options are:
TIME TREE RECONSTRUCTION: --date FILE Dates of tips or ancestral nodes --date TAXNAME Extract dates from taxon names after last '|' --date-tip STRING Tip dates as a real number or YYYY-MM-DD --date-root STRING Root date as a real number or YYYY-MM-DD --date-ci NUM Number of replicates to compute confidence interval --clock-sd NUM Std-dev for lognormal relaxed clock (default: 0.2) --date-outlier NUM Z-score cutoff to exclude outlier nodes (e.g. 3) --date-options ".." Extra options passing directly to LSD2
DISCLAIMER: Please download version 2.0.6 with new options like
--date-ci.This feature is new and might still have bugs. So suggestions and bug reports are much welcome.
Inferring time tree with tip dates
This is a common scenario e.g. in virus datasets where you have sampling time for many sequences. You need first to prepare a date file, which comprises several lines, each with a taxon name (from your sequence alignment) and its date separated by spaces, tabs or blanks. Note that it is not required to have dates for all tips. For example, this date file is part of the new corona virus dataset:
hCoV-19/Wuhan-Hu-1 2019-12-31 hCoV-19/China/WF0028 2020-02 hCoV-19/USA/WA-S88 2020-03-01 hCoV-19/USA/CA-CDPH-UC1 2020 hCoV-19/Italy/SPL1 2020-01-29 hCoV-19/Spain/Valencia5 2020-02-27 hCoV-19/Australia/QLD01 2020-01-28 hCoV-19/Vietnam/CM295 2020-03-06 hCoV-19/bat/Yunnan 2013-07-24 hCoV-19/pangolin/Guangdong 2019-02-01:2019-12-31
The date information here can be uncertain. For example, hCoV-19/China/WF0028 was sampled in Feb 2020, hCoV-19/USA/CA-CDPH-UC1 was sampled in 2020, and hCoV-19/pangolin/Guangdong was sample between 1st Feb 2019 and 31st Dec 2019. For such data range you can use “NA” to mean that the lower or upper bound is missing, e.g.:
TaxonA 2018-02-01:NA TaxonB NA:2018-03-31
which means that TaxonA was sampled after 1st Feb 2018 and TaxonB was sampled before 31st Mar 2018.
Now run IQ-TREE with:
iqtree -s ALN_FILE --date DATE_FILE
where ALN_FILE is the sequence alignment and DATE_FILE is the date file. This single command line will perform three steps: (1) find the best-fit model using ModelFinder, (2) find the maximum likelihood (ML) tree with branch lengths in number of substitutions per site, and (3) rescale the branch lengths of the ML tree to build a time tree with dated ancestral node. As output IQ-TREE will additional print three files:
ALN_FILE.timetree.lsd: The report of LSD.ALN_FILE.timetree.nex: Time tree file in NEXUS format, that can be viewed nicely in FigTree (Click on “Node Labels” on the left tab and choose “Display” as “date” in FigTree, see figure below).ALN_FILE.timetree.nwk: Time tree file in NEWICK format.
This command will automatically detect the best root position (according to LSD criterion). However, if the root is incorrectly inferred, it may produce wrong dates. Therefore, it is advisable to provide outgroup taxa if possible. In this example, we have this information, so you can use -o option:
iqtree -s ALN_FILE --date DATE_FILE -o "hCoV-19/bat/Yunnan,hCoV-19/pangolin/Guangdong"
to instruct IQ-TREE that the root is on the branch separating bat and pangolin sequences from the rest.
Alternatively you can also append the dates into the sequence names of the alignment file using the | separator, such as (assuming a FASTA file here):
>hCoV-19/Wuhan-Hu-1|2019-12-31 ...... >hCoV-19/China/WF0028|2020-02 ...... >hCoV-19/USA/WA-S88|2020-03-01 ...... >hCoV-19/USA/CA-CDPH-UC1|2020 ...... >hCoV-19/Italy/SPL1|2020-01-29 ...... >hCoV-19/Spain/Valencia5|2020-02-27 ...... >hCoV-19/Australia/QLD01|2020-01-28 ...... >hCoV-19/Vietnam/CM295|2020-03-06 ...... >hCoV-19/bat/Yunnan|2013-07-24 ...... >hCoV-19/pangolin/Guangdong|2019 ......
Then run IQ-TREE:
iqtree -s ALN_FILE --date TAXNAME -o "hCoV-19/bat/Yunnan,hCoV-19/pangolin/Guangdong"
The special keyword TAXNAME for the --date option instructs IQ-TREE to automatically extract the dates from the taxon names.
Calibrating tree using ancestral dates
Another scenario is that we have sequences from present day and want to calibrate the dates of the ancestral nodes. This will only work if you have fossil date record of at least one ancestral node in the tree. Then you again need to prepare a date file which looks like:
taxon1,taxon2 -50 taxon3,taxon4,taxon5 -100 taxon6 -10
which, for example, mean that the most recent common ancestor (MRCA) of taxon1 and taxon2 was 50 mya (million year ago) and the MRCA of taxon3, taxon4, taxon5 was 100 mya. Note that no empty space should be added to the comma-separated list of taxa, as empty space is used as a separator between taxon list and dates.
Now run IQ-TREE:
iqtree -s ALN_FILE --date DATE_FILE --date-tip 0
This means that except for taxon6, all other taxa have the date of 0 for presence.
If you know the root date, then you can set it via --date-root option.
Dating an existing tree
If you already have a tree, you can use option -te TREE_FILE to ask IQ-TREE to load and fix this tree topology:
iqtree -s ALN_FILE --date DATE_FILE -te TREE_FILE
This will work with the scenarios above, i.e., IQ-TREE will date the user-defined tree instead of the ML tree. To further speed up the process: If you know the model already, you set can it via -m option; or in a partitioned analysis, you can provide a partition file with specified models.
Obtaining confidence intervals
To infer the confidence interval of the estimated dates, use --date-ci option:
iqtree -s ALN_FILE --date DATE_FILE --date-ci 100
which will resample branch lengths 100 times to infer the confidence intervals. Note that this is not bootstrap and the method is much faster but unpublished. Roughly speaking, it is based on a mixture of Poisson and lognormal distributions for a relaxed clock model. You can control the standard deviation of the lognormal distribution via --clock-sd option. The default is 0.2. If you set a higher value, the confidence interval will become wider.
Excluding outlier taxa/nodes
Long branches may cause biased date estimates. To detect and exclude outlier taxa or nodes prior to dating, use --date-outlier option:
iqtree -s ALN_FILE --date DATE_FILE --date-outlier 3
that specifies a z-score threshold to detect outliers. The higher this value is, the more outliers will be removed from the resulting time tree.
Full list of LSD2 options
The main options in IQ-TREE provide easy access to the key LSD2 functions. If you would like more control of what LSD2 is doing, you can use the --date-options "..." command to pass any valid options to LSD2. For example, to control the way that LSD2 treats outliers, you can do this:
iqtree -s ALN_FILE --date DATE_FILE --date-options "-e 2"
A full list of the options for LSD2 can be obtained by downloading LSD2 and running lsd2 -h, the output of that command is reproduced here for convenience:
LSD: LEAST-SQUARES METHODS TO ESTIMATE RATES AND DATES - v.1.8
DESCRIPTION
This program estimates the rate and the dates of the input phylogenies given
some temporal constraints.
It minimizes the square errors of the branch lengths under normal
distribution model.
SYNOPSIS
./lsd [-i inputFile] [-d inputDateFile] [-o outputFile] [-s sequenceLength]
[-g outgroupFile] [-f nbSamplings]
OPTIONS
-a rootDate
To specify the root date if there's any. If the root date is not a
number, but a string (ex: 2020-01-10, or b(2019,2020)) then it should
be put between the quotes.
-b varianceParameter
The parameter (between 0 and 1) to compute the variances in option -v. It
is the pseudo positive constant to add to the branch lengths
when calculating variances, to adjust the dependency of variances to
branch lengths. By default b is the maximum between median branch length
and 10/seqlength; but it should be adjusted based on how/whether the
input tree is relaxed or strict. The smaller it is the more variances
would be linear to branch lengths, which is relevant for strict clock.
The bigger it is the less effect of branch lengths on variances,
which might be better for relaxed clock.
-d inputDateFile
This options is used to read the name of the input date file which
contains temporal constraints of internal nodes
or tips. An internal node can be defined either by its label (given in
the input tree) or by a subset of tips that have it as
the most recent common ancestor (mrca). A date could be a real or a
string or format year-month-day.
The first line of this file is the number of temporal constraints. A
temporal constraint can be fixed date, or a
lower bound l(value), or an upper bound u(value), or an interval b(v1,v2)
For example, if the input tree has 4 taxa a,b,c,d, and an internal node
named n, then following is a possible date file:
6
a l(2003.12)
b u(2007.07)
c 2005
d b(2001.2,2007.11)
mrca(a,b,c,d) b(2000,2001)
n l(2004.3)
If this option is omitted, and option -a, -z are also omitted, the
program will estimate relative dates by giving T[root]=0 and T[tips]=1.
-D outDateFormat
Specify output date format: 1 for real, 2 for year-month-day. By default
the program will guess the format of input dates and uses it for
output dates.
-e ZscoreOutlier
This option is used to estimate and exclude outlier nodes before dating
process.
LSD2 normalize the branch residus and decide a node is outlier if its
related residus is great than the ZscoreOutlier.
A normal value of ZscoreOutliercould be 3, but you can adjust it
bigger/smaller depending if you want to have
less/more outliers. Note that for now, some functionalities could not be
combined with outliers estimation, for example
estimating multiple rates, imprecise date constraints.
-f samplingNumberCI
This option calculates the confidence intervals of the estimated rate and
dates. The branch lengths of the esimated
tree are sampled samplingNumberCI times to generate a set of simulated
trees. To generate simulated lengths
for each branch, we use a Poisson distribution whose mean equals to the
estimated one multiplied by the sequence length, which is
1000 by default if nothing was specified via option -s. Long sequence
length tends to give small confidence intervals. To avoid
over-estimate the confidence intervals in the case of very long sequence
length but not necessarily strict molecular clock, you
could use a smaller sequence length than the actual ones. Confidence
intervals are written in the nexus tree with label CI_height,
and can be visualzed with Figtree under Node bar feature.
-g outgroupFile
If your data contain outgroups, then specify the name of the outgroup
file here. The program will use the outgroups to root the trees.
If you use this combined with options -G, then the outgroups will be
removed. The format of this file should be:
n
OUTGROUP1
OUTGROUP2
...
OUTGROUPn
-F
By default without this option, we impose the constraints that the date
of every node is equal or smaller then the
dates of its descendants, so the running time is quasi-linear. Using this
option we ignore this temporal constraints, and
the the running time becomes linear, much faster.
-h help
Print this message.
-i inputTreesFile
The name of the input trees file. It contains tree(s) in newick format,
each tree on one line. Note that the taxa sets of all
trees must be the same.
-j
Verbose mode for output messages.
-G
Use this option to remove the outgroups (given in option -g) in the
estimated tree. If this option is not used, the outgroups
will be kept and the root position in estimated on the branch defined by
the outgroups.
-l nullBlen
A branch in the input tree is considered informative if its length is
greater this value. By default it is 0.5/seq_length. Only
informative branches are forced to be bigger than a minimum branch length
(see option -u for more information about this).
-m samplingNumberOutlier
The number of dated nodes to be sampled when detecting outlier nodes.
This should be smaller than the number of dated nodes,
and is 10 by default.
-n datasetNumber
The number of trees that you want to read and analyse.
-o outputFile
The base name of the output files to write the results and the time-scale
trees.
-p partitionFile
The file that defines the partition of branches into multiple subsets in
the case that you know each subset has a different rate.
In the partition file, each line contains the name of the group, the
prior proportion of the group rate compared to the main rate
(selecting an appropriate value for this helps to converge faster), and a
list of subtrees whose branches are supposed to have the
same substitution rate. All branches that are not assigned to any subtree
form a group having another rate.
A subtree is defined between {}: its first node corresponds to the root
of the subtree, and the following nodes (if there any)
correspond to the tips of the subtree. If the first node is a tip label
then it takes the mrca of all tips as the root of the subtree.
If the tips of the subtree are not defined (so there's only the defined
root), then by
default this subtree is extended down to the tips of the full tree. For
example the input tree is
((A:0.12,D:0.12)n1:0.3,((B:0.3,C:0.5)n2:0.4,(E:0.5,(F:0.2,G:0.3)n3:0.33)
n4:0.22)n5:0.2)root;
and you have the following partition file:
group1 1 {n1} {n5 n4}
group2 1 {n3}
then there are 3 rates: the first one includes the branches (n1,A),
(n1,D), (n5,n4), (n5,n2), (n2,B), (n2,C); the second one
includes the branches (n3,F), (n3,G), and the last one includes all the
remaining branches. If the internal nodes don't have labels,
then they can be defined by mrca of at least two tips, for example n1 is
mrca(A,D)
-q standardDeviationRelaxedClock
This value is involved in calculating confidence intervals to simulate a
lognormal relaxed clock. We multiply the simulated branch lengths
with a lognormal distribution with mean 1, and standard deviation q. By
default q is 0.2. The bigger q is, the more your tree is relaxed
and give you bigger confidence intervals.
-r rootingMethod
This option is used to specify the rooting method to estimate the
position of the root for unrooted trees, or
re-estimate the root for rooted trees. The principle is to search for the
position of the root that minimizes
the objective function.
Use -r l if your tree is rooted, and you want to re-estimate the root
locally around the given root.
Use -r a if you want to estimate the root on all branches (ignoring the
given root if the tree is rooted).
In this case, if the constrained mode is chosen (option -c), method
"a" first estimates the root without using the constraints.
After that, it uses the constrained mode to improve locally the
position of the root around this pre-estimated root.
Use -r as if you want to estimate to root using constrained mode on all
branches.
Use -r k if you want to re-estimate the root position on the same branche
of the given root.
If combined with option -g, the root will be estimated on the branche
defined by the outgroups.
-R round_time
This value is used to round the minimum branch length of the time scaled
tree. The purpose of this is to make the minimum branch length
a meaningful time unit, such as day, week, year ... By default this value
is 365, so if the input dates are year, the minimum branch
length is rounded to day. The rounding formula is round(R*minblen)/R.
-s sequenceLength
This option is used to specify the sequence length when estimating
confidence intervals (option -f). It is used to generate
integer branch lengths (number of substitutions) by multiplying this with
the estimated branch lengths. By default it is 1000.
-S minSupport
Together with collapsing internal short branches (see option -l), users
can also collapse internal branches having weak support values (if
provided in the input tree) by using this option. The program will
collapse all internal branches having support <= the specifed value.
-t rateLowerBound
This option corresponds to the lower bound for the estimating rate. It is
1e-10 by default.
-u minBlen
By default without this option, lsd2 forces every branch of the time
scaled tree to be greater than 1/(seq_length*rate) where rate is
an pre-estimated median rate. This value is rounded to the number of days
or weeks or years, depending on the rounding parameter -R.
By using option -u, the program will not estimate the minimum branch
length but use the specified value instead.
-U minExBlen
Similar to option -u but applies for external branches if specified. If
it's not specified then the minimum branch length of external
branches is set the same as the one of internal branch.
-v variance
Use this option to specify the way you want to apply variances for the
branch lengths. Variances are used to recompense big errors on
long estimated branch lengths. The variance of the branch Bi is Vi =
(Bi+b) where b is specified by option -b.
If variance=0, then we don't use variance. If variance=1, then LSD uses
the input branch lengths to calculate variances.
If variance=2, then LSD runs twice where the second time it calculates
the variances based on the estimated branch
lengths of the first run. By default variance=1.
-V
Get the actual version.
-w givenRte
This option is used to specify the name of the file containing the
substitution rates.
In this case, the program will use the given rates to estimate the dates
of the nodes.
This file should have the following format
RATE1
RATE2
...
where RATEi is the rate of the tree i in the inputTreesFile.
-z tipsDate
To specify the tips date if they are all equal. If the tips date is not a
number, but a string (ex: 2020-01-10, or b(2019,2020))
then it should be put between the quotes.
Documentation
Assessing Phylogenetic Assumptions
Phylogenetic Dating
- Bayesian dating with MCMCtree
- IQ2MC workflow for time tree inference
- Estimating the gradients and the Hessian for MCMCtree dating
- Using partitions and Mixture models for approximate likelihood dating
- How to run MCMCtree
- Least Square Dating (LSD2)
- Inferring time tree with tip dates
- Calibrating tree using ancestral dates
- Dating an existing tree
- Obtaining confidence intervals
- Excluding outlier taxa/nodes
- Full list of LSD2 options
Simulating sequence alignments