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Methodological aspects in integromics: integrating multiple omics data sets
Published on Feb 17, 20152248 Views
The advent of high-throughput technologies including sequencers and array-based assays (expression, SNP, CpG) have caused the generation of humongous amounts of data often referred to as “Big Data”. T
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Chapter list
Methodological Aspects in Integromics00:00
Outline00:21
Biostatistics – Biomedicine - Bioinformatics01:28
Systems Biology and Chemical Biology01:37
Integromics02:14
Data integration: Definition02:16
What’s in a name?03:28
Multidisciplinary, interdisciplinary, transdisciplinary research04:30
Data integration: Motivation and Opportunity06:31
Is there room for data integration? - 107:30
Is there room for data integration? - 209:36
Data integration: Motivation and Opportunity11:12
So we have the motive, and the opportunity11:31
Building blocks of a “data integration” pipeline11:43
Systems information by integration16:10
Identifying the (characteristics of the) data types16:42
Building blocks of a “data integration” pipeline - 118:14
Building blocks of a “data integration” pipeline - 218:41
Building blocks of a “data integration” pipeline - 319:49
Integrative analytics - 121:25
Integrative analytics - 222:03
Finding the most appropriate method for your research question23:09
Taking baby steps: starting from GWAs23:36
Methodological challenges - a toy example 24:41
Methodological aspects: scaling up from GWAs to GWAIs - 124:43
Methodological aspects: scaling up from GWAs to GWAIs - 226:50
Practical aspects28:21
Computational Efficiency29:03
From GWAs to exomes: speed29:26
Population and patient substructures30:47
Detecting structure in patients: subphenotyping - 131:04
Detecting structure in patients: subphenotyping - 232:18
Detecting structure in patients: subphenotyping - 332:46
Detecting structure in patients / populations35:05
Meta-analysis36:22
Meta-GWAIs36:44
Dealing with increased heterogeneity37:42
Meta-GWAI studies38:30
Interpretation42:41
Statistical versus biological epistasis42:42
Replication and validation44:18
Difference between “replication” and “validation”45:42
Replication using tagSNPs46:32
Available “knowledge” about epistasis47:27
Different levels48:35
Candidate gene pairs49:28
No replication without a consensus - 151:27
No replication without a consensus - 254:41
Unable to replicate is a bad thing?58:05
Combining it all: genomic MB-MDR58:55
MB-MDR58:59
Gene-based or set-based testing01:01:21
Genomic MB-MDR - 101:03:23
Genomic MB-MDR - 201:04:43
Starting from GWAIs - Bio3’s research lines01:04:45
Integration to enhance biological network construction - 101:05:32
Methodological aspects in integromics01:06:16
Genomic MB-MDR applied to …01:07:16
Integromics: Mission ..possible?01:07:18