Comments (3)
MahShaaban
commented on September 25, 2024
The only way I can think of is to use pcr_test with the option test = 'lm'. You can include any arbitrary variable in a linear model and estimate/control for its effect.
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JacobRPrice
commented on September 25, 2024
Hi @MahShaaban , thank you for the suggestion, I can give that a try.
At this point do you have any plans on developing or expanding the pcr package to include absolute abundance calculations and associated statistical tests? If so, the inclusion of sample mass information would be best implemented at that time.
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MahShaaban
commented on September 25, 2024
I am certainly open to the idea. If you like, you can kick start this feature by opening a new issue and providing some help on how it can be implemented.
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Related Issues (20)
- 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
- Does calculated error represents Standard deviation? HOT 3
- 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
- technical replicates HOT 2
- something wrong with my data HOT 1
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