Timeline for Skew of log-normal distribution using sciPy
Current License: CC BY-SA 3.0
14 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 12, 2013 at 3:18 | history | edited | Glen_b | CC BY-SA 3.0 |
added 172 characters in body
|
| Nov 12, 2013 at 0:00 | history | edited | Glen_b | CC BY-SA 3.0 |
added 1 characters in body
|
| Nov 11, 2013 at 22:48 | comment | added | Dima1982 | I'll make a more elaborate example and post it as a separate answer (or a new question), probably tomorrow.Thank you again! | |
| Nov 11, 2013 at 22:41 | history | edited | Glen_b | CC BY-SA 3.0 |
added 111 characters in body
|
| Nov 11, 2013 at 22:40 | comment | added | Glen_b | Okay. I'll remove the last part of my answer. (Still not completely clear on what's going on with that part of your question though.) | |
| Nov 11, 2013 at 22:36 | comment | added | Dima1982 |
Actually, I am trying to make a decision like this: for one gene, if distribution is shifted to the right, assume 1 (gene is mostly 'on') and for a new value evaluate cdf(z-score-of-value). If cdf <0.2 then 1, else 0. If skewed to the left (gene mostly 'off'), then assume 0. For a new value evaluate 1-cdf(z-score-of-value) and if 1-cdf < 0.2, then assign 0, else 1. The extra example, really clarifies it. I think that if I use the Pearson moment, it should be OK for my purposes. I needed a measure that relates "most of the probability" to the mean.
|
|
| Nov 11, 2013 at 22:36 | history | edited | Glen_b | CC BY-SA 3.0 |
added 111 characters in body
|
| Nov 11, 2013 at 22:29 | comment | added | Glen_b | How does discretizing a variable relate to your questions about skewness? I am afraid I still don't understand enough about what you're doing to answer the final question about shifting to the right (on the other hand it sounds like you're satisfied so maybe it doesn't matter now). I seem to be done editing for the moment. | |
| Nov 11, 2013 at 22:26 | history | edited | Glen_b | CC BY-SA 3.0 |
added 421 characters in body
|
| Nov 11, 2013 at 22:20 | comment | added | Dima1982 | Relating to your edit, I was mixing up the population-sample quantities. I am trying to discretize gene expression data (that usually fit a log-normal distribution). So, in a sample of expressions from multiple cells, if a gene is "mostly on", give a value of 1, 0 otherwise. That was my initial idea, at least. | |
| Nov 11, 2013 at 22:14 | history | edited | Glen_b | CC BY-SA 3.0 |
added 311 characters in body
|
| Nov 11, 2013 at 22:14 | vote | accept | Dima1982 | ||
| Nov 11, 2013 at 22:14 | comment | added | Dima1982 | Thank you very much for the quick reply! I knew I was confusing something. This really clarified it! I don't have enough rep to vote your answer up, but will do so asap1 | |
| Nov 11, 2013 at 22:09 | history | answered | Glen_b | CC BY-SA 3.0 |