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

Bachelor Thesis , 2014 , 51 Pages , Grade: 165/200 (A+)

Computer Science - Bioinformatics

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.

Contents

1. Theory
1.1 Normalization
1.2 Comparison of two groups of samples
1.3 Signal Log Ratio Algorithm
1.4 Correlation (r)
1.5 Log2-transformation
1.6 Intensity ratio
1.7 Hypothesis pair
1.8 Threshold for p-value
1.9 Fold change
1.10 Time series
1.11 Microarray preparation
1.12 Probe preparation, hybridization and imaging
1.13 Low level information analysis

2. Introduction
2.1 SIRS, Sepsis and Septic Shock
2.2 Related Background
2.3 .CEL File Description
2.4 Gene Expression Omnibus (GEO)
2.5 KEGG

3. Materials methods
3.1 Data
3.2 Data Analysis
3.3 Clustering
3.4 Enrichment tests
3.5 Lagged Correlation
3.6 Additional Information

4. RESULTS
4.1 Differentially Expressed Genes
4.2 Clustering:
4.3 Regulation of some important genes
4.3.1 HLA-DMB LCN
4.3.2 Correlation of LCN 2and LTF
4.3.3 SLC4A1 IL5RA
4.4 Gender Linked Genes:
4.5 Gene Set Enrichment Analysis (GSEA)
4.5.1 Kegg Mapper
4.5.2 Glycolysis Gluconeogenesis
4.5.3 Ribosome
4.6 Toll Like Receptors Signaling Pathway and Heatmap

5. DISCUSSION

6. REFERENCES

7. SUPPLEMENTARY

• Grade: 165/200 (A+)
• Author: Deepak Tanwar (Author)
• Publication Year: 2014
• Pages: 51
• Catalog Number: V284986
• ISBN (eBook): 9783656858447
• ISBN (Book): 9783656858454
• Language: English
• Tags: comprehensive, reanalysis, genomic, storm, transcriptomic, data, integrating, clinical, varibles, utilizing, approaches