Scientific

MK5 Microarray Data


Affected Genes - Ontology Breakdown - Gene Enrichment - Proteome Analysis

These are the micro-array results of a differential gene expression microarray experiments and the subsequent analysis steps performed on them. The up/down- regulation ratio was obtained by measuring WT cells against MK5 activated cells. See material and methods for technical information as well as the data usage policy.

Ontology Breakdown

Below is a table that can help you break down the effect of the gene alteration on the bioloigcal system. To create the table below we went over all the ontology terms and counted the number of times a gene was listed in that specific class, or one of its children. As can be expected, each class will differ in its behavior. Some will have a strong average regulation, but will contain very few genes, while others will be very large and broad classes that will have a lower average regulation, but which will whos an overall effect with many genes in many subgroups being affected.

The best strategy to analyze such classes is to a) filter out all the classes for which we have too little data (less than 5 affected genes on the micro array measurement). This can be done by writing '>5' in the 'Affected Genes' field. SEcondly we might also want to look at one specific ontology at first (click on 'biological process' in the table.

Once this is done we can sort the data properly by placing the 'Average Regulation' to the left (click on the green arrows) and the '% Affected Genes' as a second. We also want to sort them descending (the grey arrow should be pointing downward).

Now we can go investigate the data by first look at broadly affected classes ('Would Be Affected Genes'>60) and progressively lowering this value (to something like 'Would Be Affected Genes'>20)


Navigation/Query Panel:
Click on the attribute name to hide/unhide it. The green arrows can be used to shift columns left/right. Exact word match is written as =..., regular expressions can be matched with ~.... To select all values larger or equal than use >.... This would be <... for values smaller or equal than. To select all values within a specific range use [...,...].
% Affected Genes Average Regulation (ratio) Would Be Affected (#genes) Class Size (#genes) Class affected Class Microarray Measured (#genes) Accession
Results: HTML CSV LaTeX Showing element 1 to 50 of 5007 in total
Class  : biological process
% Affected Genes
Average Regulation (ratio)
Would Be Affected (#genes)
Class Size (#genes)
Class
100.0000 5.835443019866943 1 1 oocyte differentiation
3.367248058319092 negative regulation of antiviral response
negative regulation of antiviral response by host
positive regulation of viral protein levels in host cell
regulation of viral protein levels in host cell
2.7504823207855225 2 2 spindle assembly
2.104278087615967 1 1 leading edge cell differentiation
1.6066848039627075 osmosensory signaling pathway
1.5708750486373901 caudate nucleus development
putamen development
1.4955823421478271 positive regulation of astrocyte differentiation
1.4335074424743652 vacuolar protein catabolic process
1.4221534729003906 serotonin transport
1.3346540927886963 pericardium development
1.2835599184036255 muscle cell fate determination
1.2769564390182495 positive regulation of cyclin-dependent protein kinase activity
1.258076786994934 nose development
1.2514674663543701 positive regulation of lymphotoxin A biosynthetic process
regulation of lymphotoxin A biosynthetic process
1.2165690660476685 synaptic vesicle targeting
1.20923912525177 nucleus accumbens development
optic cup morphogenesis involved in camera-type eye development
1.1809606552124023 cyclooxygenase pathway
66.6667 1.39005708694458 2 3 neural nucleus development
50.0000 5.835443019866943 1 2 positive regulation of meiosis
4.046511650085449 2 3 nuclear migration
3.7029240131378174 1 2 myoblast migration
3.367248058319092 2 3 positive regulation of viral genome replication
regulation of viral transcription
4 regulation of antiviral response by host
2.104278087615967 1 2 negative regulation of protein amino acid autophosphorylation
regulation of protein amino acid autophosphorylation
1.7584588527679443 L-cystine transport
sulfur amino acid transport
1.4955823421478271 regulation of astrocyte differentiation
1.3346540927886963 negative regulation of cardiac muscle cell proliferation
positive regulation of cardioblast differentiation
regulation of cardioblast differentiation
1.2983962297439575 3 5 cytokinesis after mitosis
1.258076786994934 1 2 female genitalia development
palate development
1.2514674663543701 positive regulation of T-helper 2 cell differentiation
1.2384507656097412 response to sterol depletion
1.1949561834335327 glyoxylate cycle
isocitrate metabolic process
1.1913443803787231 zygotic determination of anterior/posterior axis, embryo
1.1086714267730713 positive regulation of growth hormone secretion
regulation of growth hormone secretion
40.0000 3.9217323064804077 2 5 embryonic skeletal morphogenesis
33.3333 5.835443019866943 1 3 regulation of meiosis

Legend:
- The Average Regulation (ratio) is calculated only for the measured genes in this gene ontology term
- % Affected Genes is the % of genes in this gene ontology class that have been affected by the Mk5 alteration.
- Would Be Affected (#genes) represents how many genes of the overall class would have been affected if we measured each of them.
- The Class Size (#genes) counts the number of genes listed under the specific gene ontology term.
- Class is the GO class description.
- The Class refers to the ontology category, which can be molecular_function, biological_process or cellular_component.
- The Microarray Measured (#genes) lists how many genes of the specific ontology term were measured.
- Accession is the GO accession key.

- http://analysis.yellowcouch.org/