User: fracarb8
fracarb8 • 50
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Posts by fracarb8
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... Check the edited answer ...
written 3 days ago by
fracarb8 • 50
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... In Seurat 3, you can export the coordinates to a dataframe using `Embeddings()`.
`umapCoord <- as.data.frame(Embeddings(object = AD007[["umap"]]))`
You can then add the PC columns to the `meta.data` as you please (`cbind`, `sapply`, `paste(..,collapse=)`,...)
For example, if you only need to ...
written 5 days ago by
fracarb8 • 50
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... aren't those ID isoforms of the same genes? ...
written 27 days ago by
fracarb8 • 50
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... The problem with that is that you won't be able to know which GO term that `log2FC` is associated to. If you look at your example, `PTK2` has multiple `1s`, but only a single `log2FC`.
With `dcast` you have `NaN` if the gene is not enriched and a `logFC` value (specific for that GO term) if it is.
...
written 13 months ago by
fracarb8 • 50
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... dcast fills the table with what is passed by `value.var = `.
The data specified in your question has only 3 columns, so the only value that can be used to populate the table is `log2FC`. Which value you want the table to be filled? what are the 0-1 values in your last table?
...
written 13 months ago by
fracarb8 • 50
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... You can convert a long table to a wide one with dcast
library(data.table)
dcast(yourDF,Gene_Name~GO_term , value.var = "Log2FC",fun.aggregate = mean)
You may want to change the aggregate function depending on how you want to handle duplicated values. ...
written 13 months ago by
fracarb8 • 50
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... The TRON cell line portal contains more cell lines than CCLE, as it is built by merging CCLE with additional cell lines from Klijn et al.
It turns out it is down for maintenance, and it should be back eventually (no date as of June 2019).
...
written 16 months ago by
fracarb8 • 50
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... bash is your friend here :D
I would suggest to have a look at github as there are several gromacs wrappers (e.g. GromacsWrapper).
If you need inspiration to write your own piece of code, you can have a look at the project I used.
Note that **it is massively outdated**:
[doitGROMACS_equilib][1]
...
written 16 months ago by
fracarb8 • 50
0
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... It depends a bit where your mutations are.
The topology of your 100 proteins are likely to be exactly the same, but for few residues.
You can generate the topology for the wild-type and then replace the coordinates of the mutate residues, to obtain all the mutants you want.
The quickest way could b ...
written 16 months ago by
fracarb8 • 50
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... Why don't you simply `read.delim()` your file, save the column containing your IDs into `values` and pass it to useMart?
`data <- read.delim("/Users/amandinelecerfdefer/Desktop/rsID.txt")`
`values <- data[,1] # or use $ if the column is not the first`
`ensembl <- useMart("ENSEMBL_MA ...
written 16 months ago by
fracarb8 • 50
Latest awards to fracarb8
Scholar
3 days ago,
created an answer that has been accepted.
For A: Adding UMAP coordinates to metadata
Teacher
4 days ago,
created an answer with at least 3 up-votes.
For A: Adding UMAP coordinates to metadata
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