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 Class Average Regulation (ratio) Would Be Affected (#genes) Class Size (#genes) affected Class Microarray Measured (#genes) Accession
Results: HTML CSV LaTeX Showing element 1 to 50 of 5007 in total
Class  : biological process
% Affected Genes
Class
Average Regulation (ratio)
Would Be Affected (#genes)
Class Size (#genes)
100.0000 caudate nucleus development 1.5708750486373901 1 1
cyclooxygenase pathway 1.1809606552124023
leading edge cell differentiation 2.104278087615967
muscle cell fate determination 1.2835599184036255
negative regulation of antiviral response 3.367248058319092
negative regulation of antiviral response by host
nose development 1.258076786994934
nucleus accumbens development 1.20923912525177
oocyte differentiation 5.835443019866943
optic cup morphogenesis involved in camera-type eye development 1.20923912525177
osmosensory signaling pathway 1.6066848039627075
pericardium development 1.3346540927886963
positive regulation of astrocyte differentiation 1.4955823421478271
positive regulation of cyclin-dependent protein kinase activity 1.2769564390182495
positive regulation of lymphotoxin A biosynthetic process 1.2514674663543701
positive regulation of viral protein levels in host cell 3.367248058319092
putamen development 1.5708750486373901
regulation of lymphotoxin A biosynthetic process 1.2514674663543701
regulation of viral protein levels in host cell 3.367248058319092
serotonin transport 1.4221534729003906
spindle assembly 2.7504823207855225 2 2
synaptic vesicle targeting 1.2165690660476685 1 1
vacuolar protein catabolic process 1.4335074424743652
66.6667 neural nucleus development 1.39005708694458 2 3
50.0000 cytokinesis after mitosis 1.2983962297439575 3 5
female genitalia development 1.258076786994934 1 2
glyoxylate cycle 1.1949561834335327
isocitrate metabolic process
L-cystine transport 1.7584588527679443
myoblast migration 3.7029240131378174
negative regulation of cardiac muscle cell proliferation 1.3346540927886963
negative regulation of protein amino acid autophosphorylation 2.104278087615967
nuclear migration 4.046511650085449 2 3
palate development 1.258076786994934 1 2
positive regulation of cardioblast differentiation 1.3346540927886963
positive regulation of growth hormone secretion 1.1086714267730713
positive regulation of meiosis 5.835443019866943
positive regulation of T-helper 2 cell differentiation 1.2514674663543701
positive regulation of viral genome replication 3.367248058319092 2 3
regulation of antiviral response by host 4
regulation of astrocyte differentiation 1.4955823421478271 1 2
regulation of cardioblast differentiation 1.3346540927886963
regulation of growth hormone secretion 1.1086714267730713
regulation of protein amino acid autophosphorylation 2.104278087615967
regulation of viral transcription 3.367248058319092 2 3
response to sterol depletion 1.2384507656097412 1 2
sulfur amino acid transport 1.7584588527679443
zygotic determination of anterior/posterior axis, embryo 1.1913443803787231
40.0000 embryonic skeletal morphogenesis 3.9217323064804077 2 5
33.3333 arm morphogenesis 1.3346540927886963 1 3

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/