Does anyone have the solution to this error message?
I am working with Kallisto and Sleuth to analyze some RNA seq data. I have a control set of macula data and a set of macula data with AMD. I am trying to analyze differential gene expression between the two sets.
Design table:
sample Tissue Condition
AMD_macula.11 Macula AMD
AMD_macula.12 Macula AMD
AMD_macula.14 Macula AMD
AMD_macula.17 Macula AMD
AMD_macula.18 Macula AMD
AMD_macula.19 Macula AMD
ctrl_macula.10 Macula nodisease
ctrl_macula.13 Macula nodisease
ctrl_macula.15 Macula nodisease
ctrl_macula.16 Macula nodisease
ctrl_macula.4 Macula nodisease
ctrl_macula.6 Macula nodisease
I have created my sleuth object and now I am trying to fit the models so I can run linear regression and wald tests.
so <- sleuth_fit(so, ~sample + Condition,'full')
so <- sleuth_fit(so, ~Tissue, 'Tissue')
models(so)
When running these, I cannot get past creating the first model because I am getting this error that is saying that the system is computationally singular.
> so <- sleuth_fit(so, ~sample + Condition,'full')
Error in solve.default(t(X) %*% X) :
system is computationally singular: reciprocal condition number = 3.82836e-18
Does anyone know how to solve this? I believe something is wrong with my design table, but I cannot think of how to fix it.
Thanks!
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scottschu97 •
Is "sample" just a unique sample identifier?? Then it should not be included as a batch variable and you should drop it from your sleuth_fit call. Also why are you including tissue if they are all from the same tissue, if there is no variability then there is no point in including it as a batch variable.. A meaningful batch variable should be a factor variable with multiple samples per factor.
Try:
so <- sleuth_fit(so, ~ Condition, 'full')
so <- sleuth_fit(so, ~ 1, 'reduced')
Thank you! This helped!
If I did have samples with different tissues as well should I call:
so <- sleuth_fit(so, ~ Tissue, ~ Condition, 'full')
so <- sleuth_fit(so, ~ 1, 'reduced')
The full model should only be testing the effect of condition not Tissue + condition, so you would need to add Tissue to the reduced model.
so <- sleuth_fit(so, ~ Tissue, ~ Condition, 'full')
so <- sleuth_fit(so, ~ Tissue, 'reduced')
Thank you! The help is much appreciated!
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It seems that there is a problem with the code. And I see you already posted something over Sleuth's google group. I think the best option here is to wait for the sleuth's development team to give you some advice