Result Objects

Network File

network_file_name = "network.tsv"

The network.tsv is a long-format TSV file containing Regulator -> Target edges. This TSV file is sorted by the confidence score of the regulator (TF) -> target (gene) edge, from largest to smallest.:

target         regulator       combined_confidences    gold_standard   precision       recall      MCC         F1
BSU24750       BSU04730        0.999986                1               1               0.00165     0.04057     0.003295
BSU13020       BSU04730        0.999984
BSU09690       BSU04730        0.99998
BSU06590       BSU04730        0.999978
BSU18510       BSU04730        0.999976
BSU25800       BSU25810        0.999975

If the gene and TF are in the gold standard, the gold standard for this edge is reported (1 if present, 0 if not present), and the model performance is calculated. The Precision, Recall, MCC, and F1 scores are calculated assuming that all edges above a row (with greater confidence scores) are predicted TF -> Gene interactions, and all values below are predicted to not be TF -> Gene interactions. Rows which do not contain any gold standard (either 1 or 0) indicate that the regulator or the target are not in the Genes x TFs gold standard matrix. These rows will not be scored.

Also included is a column indicating if the network edge was in the prior (1, 0, or not present if the gene or TF were not present in the prior network). The beta.sign.sum column is the number of times the model coefficient occurred and the sign (positive model coefficients will be reported as a positive value, and negative model coefficients will be reported as a negative value). The var.exp.median column reports the median amount of variance in the gene explained by the regulator.

InferelatorResults

class inferelator.postprocessing.InferelatorResults(network_data, betas_stack, combined_confidences, metric_object, betas_sign=None, betas=None, priors=None, gold_standard=None)

For network analysis, the results produced in the output_dir are sufficient. Model development and comparisons may require access to values that are not written to files.

An InferelatorResults object is returned by the workflow.run() methods

A list of InferelatorResults objects is returned by the CrossValidationManager.run() methods

This object allows access to most of the internal values created by the inferelator.

name

Results name, usually set to task name. Defaults to None.

network

Network dataframe, usually written to network.tsv.gz

betas_sign

The aggregate sign of non-zero betas. This is a dataframe which is Genes x TFs

betas_stack

Count of non-zero betas. This is a dataframe which is Genes x TFs

combined_confidences

Confidence scores for tf-gene network edges. This is a dataframe which is Genes x TFs

tasks

Task result objects if there were multiple tasks. None if there were not. This is a dict, keyed by task ID