COPAP Server - Co evolution of Presence-Absent Patterns
CoPAP Logo Co-evolution of Presence-Absence Patterns (Research web site, Pupko lab)

Type your Presence-Absence data (FASTA or NEXUS or PHYLIP formats only)

Required input: The presence and absence matrix. ("1" and "0" or missing data "-")
Note: presence/absence within a genomes is coded similarly to DNA or amino acids within a gene (e.g., as rows in the Fasta file)

Upload your Presence-Absence file (FASTA or NEXUS or PHYLIP formats only)    

Type your phylogenetic tree (Optional)

Optional and recommended input: the assumed tree topology (with or without branch lengths)

Upload phylogenetic tree file      

The format of the phylogenetic tree is:

Type your characters annotation (e.g., genes description). (Optional)

A tab-delimited file with header that includes annotation information for genes/positions in the presence-absence data.
One line for each gene/position.
For format example Use Load an example.

Upload your characters annotation file (Optional)

(+) Co-evolution computation
Simulations-based inference of significant co-evolutionary interactions

Co-evolutionary interactions significance level (alpha)
Minimal value for reported co-evolutionary interactions after correction for multiple tests (i.e., the False Discovery Rate cutoff is a lower value derived from the number of tested interactions).
If '1' is selected, all possible co-evolutionary interactions are computed and reported.

Accuracy level of co-evolution inference
Higher accuracy level allow better estimation of the statistical significance for reported co-evolutionary interactions, but result with longer running duration.

Log verbosity level

(+) Advanced co-evolution parameters
Set manually the minimal number of events required in characters to look for co-evolution Yes   No

Minimal number of events required in characters to look for co-evolution
If character (e.g., genes) have too few evolutionary events, significant co-evolutioanry interactions can not be inferred and thus are omitted)

(+) Evolutionary model
The probabilistic model describing the gain and loss dynamics

Rate distribution
The evolutionary model determines how variability among positions in evolutionary rates is modeled
  1. "Equal rate for all characters": assume that a single evolutionary rate characterizes all sites.
  2. "Gamma": among site rate variation, assuming that the rate is gamma distributed
  3. "Gamma plus invariant category": gamma distributed with an additional invariant rate category (rate~zero)

gain & loss rates
  1. "Variable rate among sites": gain and loss probabilities may be different but the gain/loss ratio is identical across all sites.
  2. "Variable gain/loss ratio (mixture)": gain/loss ratio varies among sites.

gain rate defines 0 => 1 dynamics, while loss rate defines 1 => 0 dynamics.

(+) Correction for un-observable data
Likelihood correction is used when specific data not included in the data, such as position absent from all species.

Minimum number of ones
If zero is selected the model allows sites with only zeros to appear (do not account for un-observable data). Select more than one if singletons are also un-observable.

Minimum number of zeros
If zero is selected the model allows sites with only ones to appear. Select one if variable sites are required (e.g., for indel data).

(+) Estimation of model parameters
The parameters of the evolutionary model are estimated from the data.
Parameters include: gain/loss ratio, shape of the rate distributions, and branch lengths.

Estimate branch lengths using likelihood Yes   No
Likelihood estimation of branch lengths can be avoided and the input branch lengths or initial estimation is used.

Optimization level
Running times can be modified by changing the optimization level.

Number of rate categories
The continues gamma distribution is approximated with discrete number of categories.

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