The KLAB Toolbox: A Suite of In-house Software Applications for Epigenetic Analysis

Abstract

Systems biology presents a new paradigm for elucidating the processes required to organize and sustain life. We now have access to whole genome sequences, gene expression data for multiple cell types, and databases for regulatory elements governing these genes. These resources make it feasible to identify conserved genomic sequences across multiple species, transcription factors regulating the expression of genes with similar expression patterns within a given cell type and to compare expression levels of specific genes between normal and diseased cellular states. In order to utilize this wealth of information, new computational tools that integrate these datasets in a genome-wide context are required. Using the protamine cluster as an example, we present a series of in-house applications that we have developed to integrate, contextualize and visualize datasets across multiple hierarchies.

Computational identification of transcription frameworks of early committed spermatogenic cells

“…This approach was adopted to assess whether other trans-acting factors may be involved in spermatogenic gene expression. A novel algorithm was used to determine over-representation of TF modules of co-expressed genes (Lu et al 2006a; Naismith et al 2008) from two independent microarray datasets for the first wave of murine spermatogenesis. Transcription frameworks governing the expression of spermatogenic genes from spermatogonia to spermatocytes were identified.…”