I have repeated multivariate microRNA data (N=192 miRNAs) obtained from an RT-qPCR project that include two experimental groups (control and disease) measured after three different conditions (baseline (Day1), treatment_1 (Day2) and treatment_2 (Day3). There are three possible options for normalization: external spikes, reference mIRNAs or global mean. The question is how I can normalize the data to take different sample input (identical input volumes were used during RT reactions) into account without removing certain effects that may occur due to the treatments (time variable) or the group. One idea would be to split the data according to the time variable and to apply GeNorm/NormFinder only to the baseline data set. Then the data from Day2 and Day3 would be normalised by using the values from the Reference miRNAs identified from the baseline data (Day1). The idea is two use repeated ANOVA to identify 1) differences between groups at the different time points and 2) between the different time points.
Best,
Johannes
http://wwhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2327352/pdf/844.pdfw.ncbi.nlm.nih.gov/pmc/articles/PMC2327352/pdf/844.pdf
u can refer this article
https://www.google.se/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0ahUKEwjgtp22-O_MAhWLFZoKHdlxByIQFghBMAQ&url=http%3A%2F%2Fbib.oxfordjournals.org%2Fcontent%2Fearly%2F2015%2F08%2F03%2Fbib.bbv056.full&usg=AFQjCNGE2zLybroAKFwvOALBzOaAkfKTww&cad=rja
https://www.google.se/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&uact=8&ved=0ahUKEwjgtp22-O_MAhWLFZoKHdlxByIQFggwMAI&url=https%3A%2F%2Fwww.biogazelle.com%2Ffour-tips-rt-qpcr-data-normalization-using-reference-genes&usg=AFQjCNHg4wzpdzX8TkC-3G8U90uwnW0IaQ
These are two links for two interesting articles, I hope this helps.
- Badges
- Science topic
- Similar topics
- Biological Science
- Biochemistry
- Biomolecules
- Nucleic Acids
- RNA
- Small RNA
- microRNA