Lecture 9 Analyses of temporal Data Flashcards
(12 cards)
Why do we need to normalise?
To measure real biological changes by minimising processing or
experimental variation
To express data so that relative gene expression levels can be
compared between experiments
How is QPCR normalised
Scaling factor normailisation
not good- assume variation is same across all genes
How arrays are normalised within?
values logged(important to disregard absolute magnitude) Normal Distrubtion is checked and variation is corrected.
How are array normalised between them?
All array distrubutions are the same and corrects for array bias
Quantile normalisation Gene-Row Array no- columns method colums arranged low to high, rows averaged and substituded in and reordered
What to know after normalisation
Scale of response and effect(how many genes and to what level are they regulates, and significance.
How similar are responses
Most impotant master regulator?
First Step- statistical test
ANOVA test over our cell samples do genes change
Tools allow us to
Multuple testing correction- to reduce false positive
Stats tests to reveal what genes are significantly changing
and tools to analyse an patters
After stats how to check sata is sound
Other methods- QPCR
compare to other datasets
How to analyse the data- what biological is regulated?
View funtions of genes and analyse gene ontology(location and function) to look for groups of genes that may be clustered due to response.
Similiar Responses
Cluster genes and experiments on a heat maps in terms of response.(repressed and not)
How to identify mechanism of regulations: downstream regulatory targets
look for trancripton factor binding motifs(TRANSFAC) in promotor regions,
Upstream regulators identifications(transcription facters
Compare promotors and identify common bases of significance and score using Position specific scoring matrix(PSSM).
Use temporal profiling experiments to identify coexpression of genes- with consideration to time delay correlation using TCAP
How to follow up on experiement
Downstream CHIP- chromatin immunoprecipitation.
