Using custom R scripts, all fold changes were calculated using a one read pseudocount as lfc=log2((1+condictionRPKM)/(1+referenceRPKM)).
All RiP counts were normalized by calculating the lfc against the corresponding input.
The four RiP signals are defined as follows:
M2RIP_WT vs InputWT lfc (M2RIP_vs_WT_fc),
M2RIP_Tg6105 vs InputTg6105 lfc (M2RIP_vs_Tg6105_fc),
HuR_RIP_C57 vs InputC57 lfc (HuR_RIP_C57_vs_C57_fc),
IgG_RIP_C57 vs InputC57 lft (IgG_RIP_C57_fc).
The final foldchange ratios are defined as:
M2RIP_WTvsInputWT_vs_M2RIP_Tg6105vsInputTg6105_FC = M2RIP_WT_fc - M2RIP_Tg6105_fc,
HuR_RIPC57r_vs_IgG_RIP_C57_FC = HuR_RIP_C57_fc - IgG_RIP_C57_fc.

Significance of the fold changes was assessed using two-sided Student-s t-tests and adjusted p-values were calculated using the Benjamini and Yekutieli method [3] to compensate for multiple testing.


t-tests:
M2RIP_WTvsInputWT_vs_M2RIP_Tg6105vsInputTg6105
HuR_RIPC57rVSinput_vs_IgG_RIPC57VSinput

Foldchange ratios: