Extracto
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
- Citar trabajo
- Deepak Tanwar (Autor), 2014, Comprehensive Reanalysis of Genomic Storm (Transcriptomic) Data, Integrating Clinical Varibles and Utilizing New and Old Approaches, Múnich, GRIN Verlag, https://www.grin.com/document/284986
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