TY - JOUR AU - Nia, Anna M. AU - Chen, Tianlong AU - Barnette, Brooke L. AU - Khanipov, Kamil AU - Ullrich, Robert L. AU - Bhavnani, Suresh K. AU - Emmett, Mark R. PY - 2020 DA - 2020/03/20 TI - Efficient identification of multiple pathways: RNA-Seq analysis of livers from 56Fe ion irradiated mice JO - BMC Bioinformatics SP - 118 VL - 21 IS - 1 AB - mRNA interaction with other mRNAs and other signaling molecules determine different biological pathways and functions. Gene co-expression network analysis methods have been widely used to identify correlation patterns between genes in various biological contexts (e.g., cancer, mouse genetics, yeast genetics). A challenge remains to identify an optimal partition of the networks where the individual modules (clusters) are neither too small to make any general inferences, nor too large to be biologically interpretable. Clustering thresholds for identification of modules are not systematically determined and depend on user-settable parameters requiring optimization. The absence of systematic threshold determination may result in suboptimal module identification and a large number of unassigned features. SN - 1471-2105 UR - https://doi.org/10.1186/s12859-020-3446-5 DO - 10.1186/s12859-020-3446-5 ID - Nia2020 ER -