Data Analysis
Data analysis is critical, since any error introduced in the data analysis part will result in biologically insignificant results. In data analysis, the information from the raw data file is further processed to yield meaningful biological results. This part includes data normalization, flagging of the data, averaging the ratio for replicates, clustering of similarly expressed genes, etc. Data has to undergo normalization before further analysis. Normalization removes the non-biological variation between the samples. After the normalization, the ratio is calculated for each gene in the replicate. Based on the ratio, differentially regulated genes are determined. There are various statistical analyses which are also done for confidence analysis. Each replicate data is also examined for various experimental artifacts, bias by computing parameters related to intensity, background, flags, spot details, etc.
Read more about this topic: Gene Chip Analysis
Famous quotes containing the words data and/or analysis:
“Mental health data from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”
—Grace Baruch (20th century)
“A commodity appears at first sight an extremely obvious, trivial thing. But its analysis brings out that it is a very strange thing, abounding in metaphysical subtleties and theological niceties.”
—Karl Marx (1818–1883)