Question

Why is it important to normalize the transcript data?

		To increase the number of samples across the whole data set.
		To remove errors caused by different efficiencies of dye incorporation into the samples.
		To increase the amount of transcripts included in the data analysis.
		To eliminate complementary DNA molecules introduced during the cloning process.

The number of times a gene is over- or under-expressed compared to some baseline such as a control is called:

		Saturation point.
		Probability value.
		Fold change.
		Scaling factor.

Answer 1

1) Normalisation is a very important step in post experiment data processing to ensure there is a fair comparison of the gene expression profiles without any bias. It involves removal of any bias by the physical or chemical structure of the gene. Even bias can arise during preparation and sequencing of the batches. perfect control of all factors is out of our hands but it can be minimalised. Mainly it ensures that all values can fit into a common scale without distortion of differences in the range of values.

In this case it is used to eliminate the complementary DNA molecules which might have been introduced during cloning.

2) The no of times a gene is over expressed or under expressed compared to the baseline control is called as fold change.

It is expressed in terms of multiples or fold increase. It is compared by the measurements taken before and after a particular treatment. It is usually used to denote the data obtained from microarrays and any RNA seq experiments. The values are plotted on a log scale since the values are exponential and in terms of fold rises.