sankaranlab / scavenge Goto Github PK

Hello,
First, thanks for developing a new method for overcoming the data sparsity of scATAC!
We were suffering the same issue...

My pipeline is using archR and I successfully exported peakmatrix and import it to SCAVENGE.
I have 2 questions for running SCAVENGE on my sample.

1. my archR object is made using hg38, so my peakmatrix is hg38 mapped.
   If I liftover GWAS SNPs from hg19 to hg38, is it possible to run SCAVENGE on my hg38 mapped peakmatrix?

2. I'm trying to generate trait_file from GWAS summary statistics file which I want to use.
   I understood that to run SCAVENGE, I have to calculate each GWAS SNP's posterior probability of causality.

I tried to find how to generate trait_file from GWAS summary statistics file, but I couldn't find it...
So, is there any instructions for it?

Thanks.

Hi Fulong,

Thanks for developing SCAVENGE! I am trying to do cell enrichment with the help of it but met an input issue.

I extracted peakmatrix from our ArchR object.
peakmatrix <- getMatrixFromProject(projHeart,useMatrix = "PeakMatrix") and used it as the input of SCAVENGE following your tutorial.
The projHeart we used was processed similarly with your COVID data in the SCAVENGE paper. The finemapping data we used currently are tutorial data in SCAVENGE package.

When I tried to run computeWeightedDeviations(peakmatrix, trait_import), it returned

Error in (function (cond)  : 
  error in evaluating the argument 'object' in selecting a method for function 'getFragmentsPerPeak': "counts" %in% assayNames(object) is not TRUE

I am wondering if I extract peakmatrix correctly from the ArchR object. Do you have some suggestion on how to extract the input of SCAVENGE?

Any suggestion would be appreciated!
Thank you!
Xiaotong

Hi, thanks for this great tool! I am facing an error during permutation analysis:

Stationary step: 74
Stationary Delta: 9.83820972996253e-06
Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, :
arguments imply differing number of rows: 0, 199764
Calls: get_sigcell_simple ... as.data.frame -> as.data.frame.list -> do.call ->

Hi,
I am trying to reproduce the fine mapping results for your COVID19 analysis, but I am not able to get the same sentinel SNPs as reported. Would it be possible for you to share the reference panel and script used by you?
Thanks

Hello,

I run the same code by twice. I did not change anything. And I set the same seed number like your examples.
But I got the different result of "true_cell_top_idx" for each cell. Is this a bug? Or is it because of the permutation test method?

Best

Hi Sankaran Lab,

Is there an R version that you would recommend/is a dependency? I've been trying to install some of the dependencies but I'm running into problems mainly with chromVAR. I've been following instructions on Bioconductor to install chromVAR (https://bioconductor.org/packages/release/bioc/html/chromVAR.html) and it does say that R >=3.4 is ok but I'm wondering if it's better to use an R version closer to R 3.4.0? Currently I don't have the error warnings to share but I'm in the process of re-running the installation of chromVAR with R 3.5.1. I'll update soon with those error messages.

Thanks in advance,

Joaquin

Hello,

I was wondering if the model's assumption holds for scRNA-seq data?

Best,
Chang

Hello Fulong,
SCAVENGE is a good tool deciphering the function of genetic variant at single-cell level.
I have 2 questions about the algorithm of SCAVENGE.
1: what is the binarized sparse matrix?
2: you used TF-IDF to calculate the weight for each feature. it seems that the IDF in your paper looks a little different from (log(N/(dfi+1))).

This wiki page seems to be missing its contents:

https://github.com/sankaranlab/SCAVENGE/wiki/%5BSCAVENGE-L%5D-Analysis-for-DNA-mutation-based-lineage-tracing

As a side note, you may want to consider turning your Wiki pages into additional vignettes so they can all be found in one place (GitHub Pages once we merge this PR #10 ), a and are automatically updated and checked for bugs in future versions.