Towards Analysis of SMiLE-seq raw data with the ultimate goal of identification of binding sites of the poorly characterized transcription factors

SMiLE-seq is a new effective experimental method for transcription factor (TF) binding site sequence inference. Still, some TFs are challenging to analyze. We hope to improve the method by using modern statistical and deep learning approaches in both experiment design and the subsequent data analysis.

Deliverables:

  • a tool for inferring binding motifs that cover the sequence space representatively
  • GUI for analysis and analysis improvement
  • “denoisifier” – a tool to use prior to the HMM-based analysis

Milestones:

Open access tools for effective management of ELIXIR Nodes based on collaborative work developed in ELIXIR-CONVERGE, RITRAIN, RItrainPlus and EMMRI

The OATEN staff exchange aims at familiarising Nodes with open access tools for effective ELIXIR Node management. Several workshops are planned for the spring, together with the CONVERGE WP2 ELITMa program, covering strategic management, financial management and project management.