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

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.

Product details

• Authors: Deepak Tanwar
• Publisher: Grin Verlag
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2015
• EAN: 9783656858454
• ISBN: 978-3-656-85845-4
• No. of pages: 56
• Dimensions: 148 mm x 210 mm x 4 mm
• Weight: 96 g
• Illustrations: 10 Farbabb.
• Series: Akademische Schriftenreihe; Akademische Schriftenreihe Bd. V284986; Akademische Schriftenreihe; Akademische Schriftenreihe Bd. V284986
• Subjects: Guides; Natural sciences, medicine, IT, technology > IT, data processing > Miscellaneous