Im using wild type SW620 cancer cell line and shCD25 SW620 cells.
I want to show the significant difference in the cell viability between both the cell lines to the chemotherapeutic drug treatment.
I'm using wild type SW620 cancer cell line and shCD25 SW620 cells. Especially, I want to show the statistically significant points in my graph ( I want to annotate asterisks(*, ** ) in my graph for each concentrations) so how can I perform the statistical analysis for each concentration.
im having two different samples and 5 drug concentrations, can i use one way anova for that? and im not sure about how to get p values for cell viablity % of each concentration in the two samples?
I assume that you measure cell viability at various times(like a growth curve?). Thus I recommend a multivariate(the 2 samples) growth curve model. See:
https://www.google.com/search?rlz=1C1CHBF_enUS847US847&ei=Xi1kXfOzKoOasQWBxKeIBw&q=multivariate+growth+curve+model&oq=multivariate+growth+curve+model&gs_l=psy-ab.3..0i22i30l2.1623971.1652603..1654087...0.0..1.177.5248.0j38......0....1..gws-wiz.......33i22i29i30j0j0i10j0i131.Ie5IsH5u_2s&ved=0ahUKEwjz2qiqnaHkAhUDTawKHQHiCXEQ4dUDCAo&uact=5
Best wishes, David Booth
One-way ANOVA is the way to go I think, but I think you can also run multiple t-test in addition, to compare both groups for each concentration, with correcting using the Holm-Šídák method
https://www.graphpad.com/guides/prism/7/statistics/index.htm?stat_options_for_multiple_t_tests.htm
IMO, one way ANOVA would be a poor choice. For another ref. on Growth Curve models see: https://b-ok.cc/book/2335719/246171
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