`iggy` + `optgraph`

iggy and optgraph are tools for consistency based analysis of influence graphs and observed systems behavior (signed changes between two measured states). For many (biological) systems are knowledge bases available that describe the interaction of its components in terms of causal networks, boolean networks and influence graphs where edges indicate either positive or negative effect of one node upon another.

iggy implements methods to check the consistency of large-scale data sets and provides explanations for inconsistencies. In practice, this is used to identify unreliable data or to indicate missing reactions. Further, iggy addresses the problem of repairing networks and corresponding yet often discrepant measurements in order to re-establish their mutual consistency and predict unobserved variations even under inconsistency.

optgraph confronts interaction graph models with observed systems behavior from multiple experiments. opt_graph computes networks fitting the observation data by removing (or adding) a minimal number of edges in the given network.

Downloads

Precompiled binaries for 64bit linux and macOS can be found on the release page
Iggy user guide
Sample data demo_data.tar.gz

Compile yourself

Clone the git repository:

git clone https://github.com/bioasp/iggy.git
cargo build --release

The executables can be found under ./target/release/

Iggy

Typical usage is:

iggy -n network.cif -o observation.obs -l 10 -p

For more options you can ask for help as follows:

> iggy -h
iggy 2.2.1-dev
Sven Thiele <sthiele78@gmail.com>
Iggy confronts interaction graph models with observations of (signed) changes between two measured
states (including uncertain observations). Iggy discovers inconsistencies in networks or data,
applies minimal repairs, and predicts the behavior for the unmeasured species. It distinguishes
strong predictions (e.g. increase in a node) and weak predictions (e.g., the value of a node
increases or remains unchanged)
USAGE:
    iggy [OPTIONS] --network <FILE>
OPTIONS:
    -a, --auto-inputs                Declare nodes with indegree 0 as inputs
        --depmat                     Combine multiple states, a change must be explained by an
                                     elementary path from an input
        --elempath                   Every change must be explained by an elementary path from an
                                     input
        --founded-constraints-off    Disable foundedness constraints
        --fwd-propagation-off        Disable forward propagation constraints
    -h, --help                       Print help information
        --json                       Print JSON output
    -l, --show-labelings <N>         Show N labelings, default is OFF, 0=all
        --mics                       Compute minimal inconsistent cores
    -n, --network <FILE>             Influence graph in CIF format
    -o, --observations <FILE>        Observations in bioquali format
    -p, --show-predictions           Show predictions
        --scenfit                    Compute scenfit of the data, default is mcos
    -V, --version                    Print version information

Optgraph