*Last update: Jun 3, 2020, Contributors: M Bui, Rob Lanfear*

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.

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.

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.

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.

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.

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.

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.
```