Python implementation of NetICS (Network-based Integration of Multi-omics data).
$ pip install neticspyNetICS performs a per sample bidirectional network diffusion-based method for prioritizing genes based on their proximity to upstream aberration events and to downstream differentially expressed genes and proteins in an interaction network. The sample-specific gene lists are integrated into an overall ranked list of genes using rank aggregation technique.
There are two subcommands: neticspy diffuse and neticspy rank.
Prepare diffusion matrix for given network and restart probability. This subcommand will produce .npz file containing precomputed forward/backward diffusion matrices.
$ neticspy diffuse --adj ADJ \
--beta BETA \
--output OUTPUT
Arguments
-j ADJ, --adj ADJ: Adjacency matrix of the directed interaction network. (separted by tab)
-b BETA, --beta BETA: Restart probability for the insulated diffusion. Default: 0.4 (For the network from Wu et al., 2010)
-o OUTPUT, --output OUTPUT: Output filename for diffusion matrix in .npz format.
Run core NetICS algorithm and rank genes by their mediator effect. This subcommand will produce two comma-separated tables: raw result containing sample-gene-diffusion score triplets (raw.txt), and aggregated gene rankings (rank_aggregated.txt) that allow cohort-wise gene prioritization.
$ neticspy rank --aberration ABERRATION \
--diffusion-matrix DIFFUSION_MATRIX \
--network NETWORK \
--degs DEGS \
--output OUTPUT \
Arguments
-a ABERRATION, --aberration ABERRATION: Input two-column table (without headers) containing genetically aberrant genes for each sample. It contain two columns that map every gene (1st column) to the samples that it is genetically aberrant (2nd column).
-f DIFFUSION_MATRIX, --diffusion-matrix DIFFUSION_MATRIX: Path to .npz file for diffusion matrix.
-n NETWORK, --network NETWORK: Input file that contains the list of the genes that are present in the network. (same order with adjency matrix)
-d DEGS, --degs DEGS: List of the names of predefined differentially expressed genes. (same format with aberration file)
-o OUTPUT-PREFIX, --output-prefix OUTPUT-PREFIX: Prefix of the output file to save raw NetICS result and aggregated ranks.
-v, --verbose: Increase verbosity.
As an ordinary python package
import neticspy
netics_result = neticspy.netics_fun(
filename_aberration,
filename_network_genes,
output,
filename_deg_list,
restart_prob=0.4,
)
The default value of beta (restart probability) is 0.4.
Dimitrakopoulos, Christos, et al. "Network-based integration of multi-omics data for prioritizing cancer genes." Bioinformatics 34.14 (2018): 2441-2448.