Comments (3)
Hi @shubham7193
Thanks for reaching out. As explained in the package vignette the error term in the model is given by the square root of the sum of the squared standard deviation of the gene of interest and the reference or
().
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Hi,
Thanks for your reply. I am still confused because if this formula is being used for error then the value of the error would be the same for both control and treated samples?
Also, after plotting the pcr_analyze, it plots upper and lower values on the error bars, how can we plot SD values on the graph?
Please do let me know if my question is not very clear.
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- No. The control condition is not calibrated by anything (or by itself sot to speak), so the error term is the standard decision. For the other conditions, the error is propagated, that is taking into account the error in the control condition, hence that formula.
- To use the plotting option you have to use the error term as calculated. In the vignette, I reference a paper on this model where the recommendation was to do error propagation whose interpretation doesn't differ much from the standard deviation.
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Related Issues (20)
- Installation Error HOT 1
- NA value HOT 1
- Aggregate in .pcr_average HOT 2
- pcr HOT 3
- use pcr package for three sample group experiment HOT 2
- Negative lower value while analysing the using standard curve HOT 1
- Factor in amplification efficiency HOT 2
- Rsquared not calculated HOT 6
- `group_var` don't support variable names with `_` (underscore) HOT 2
- CpAverage or CrossingPoint HOT 6
- How to calculate the R2 for targets that have different number of replicates? HOT 3
- pcr_wilcox function HOT 4
- Add p-values on the plot HOT 2
- Importing from QuantStudio file? HOT 1
- Use column in data table for grouping when column name is passed as string to group_var HOT 2
- rOpenSci review for qPCR package HOT 4
- SEM instead of SD HOT 2
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