Timeline for Regressing out unwanted sources of variation in single cell RNA-seq data
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| Apr 24, 2018 at 16:16 | answer | added | swbarnes2 | timeline score: 2 | |
| Apr 19, 2018 at 10:10 | comment | added | Eli Korvigo | If I understand you correctly, "I want to regress out the variation caused by the number of UMI's and the percentage of mitochondrial genes" means that you want to mitigate the constrained geometry arising from multinomial sampling (aka the unit-sum problem). There are multiple transforms that can alleviate certain effects of compositionality (alr, clr, iqlr) or project the data into an unconstrained Euclidean space (ilr). The choice depends on subsequent analyses and their properties. ALDEx2, a widely used RNA-seq package, uses clr and iqlr. Take note, that they all assume certain properties. | |
| Apr 19, 2018 at 10:02 | comment | added | DCZ | yes mRNA counts, as I mentioned in the title. What regression technique is applicable for compositional data? | |
| Apr 19, 2018 at 9:59 | comment | added | Eli Korvigo |
What do you mean by single cell count data? If you mean mRNA counts, then your data are compositional and should be treated as such.
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| Apr 19, 2018 at 9:36 | answer | added | jxx_fa | timeline score: 0 | |
| Apr 18, 2018 at 22:34 | answer | added | gringer♦ | timeline score: 2 | |
| S Apr 18, 2018 at 15:45 | history | suggested | gc5 | CC BY-SA 3.0 |
fix spelling
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| Apr 18, 2018 at 15:42 | review | Suggested edits | |||
| S Apr 18, 2018 at 15:45 | |||||
| Apr 18, 2018 at 15:04 | review | First posts | |||
| Apr 24, 2018 at 11:04 | |||||
| Apr 18, 2018 at 14:58 | history | asked | DCZ | CC BY-SA 3.0 |