Comprehensive Reanalysis of Genomic Storm (Transcriptomic) Data, Integrating Clinical Varibles and Utilizing New and Old Approaches

By Deepak Tanwar

Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 165/200 (A+), language: English, abstract: Aim: I sought to determine trauma-specific transcriptomic signatures for septic sub-cohorts. Methods: In retrospective large-scale data analysis, I applied (old and new methods), including lagged correlation between transcripts and clinical subtype counts (by integrating over 800 samples from trauma patients). Results: Focussing on novel pathways and correlation methods we revealed (persistently down-regulated) ribosomal genes and changed time profiles of metabolic enzyme precursors /transcripts. Candidates associated to insulin signalling, including HK3, hinted towards "metabolic syndrome". Correlation analysis yielded robust results for LCN2 and LTF (r>0.9), but only moderate associations to subtype counts (e.g. top-performing r (Eosinophil, IL5RA)>0.6). Discussion: Gene Centred Normalisation Reduces Ambiguity and Improves Interpretation.

• Format: Paperback
• Language: English
• ISBN: 3656858454
• ISBN13: 9783656858454
• Release Date: January 2015
• Publisher: Grin Verlag
• Length: 56 Pages
• Weight: 0.19 lbs.
• Dimensions: 0.1" x 5.8" x 8.3"