tiroshlab / 3ca

Code for reproducing the analysis in Gavish et al. "The transcriptional hallmarks of intra-tumor heterogeneity across a thousand tumors".

3ca

This repository contains code relating to the Curated Cancer Cell Atlas (3CA), including code for reproducing analyses and figures on the 3CA website, and code for reproducing the analysis in Gavish et al. "The hallmarks of transcriptional intra-tumor heterogeneity".

Source code for Gavish et al.

Code for reproducing the analyses in the Gavish et al. study is contained in the ITH_hallmarks directory.

3ca's Issues

R Package Missing

To support the use of this framework by future studies, we provide software to quantify and visualize the MPs reported here in any new scRNA-seq dataset.

I was hoping to find a comprehensive R package, but I can only see analysis scripts and undocumented functions.

Gene Set Enrichment Analysis

Hi,
in the paper and also looking at the code, is not clear to me how you do the gene set enrichment analysis. How do you rank the genes? Based on which metric?
Thank you!

Example data not working

Dear Tirosh Lab,

I was trying to replicate the code using the example dataset. I used the same parameters as you did however, in Generate_Meta_Programs.R, the "Cluster_list" (generated between line 64 and 135) list that I obtain is empty.
Could you check if you can replicate this issue on your end ?

Best,

Kerim

How to prepare the Genes_nmf_w_basis_example.RDS for generating MPs?

Input:

Genes_nmf_w_basis is a list in which each entry contains NMF gene-scores of a single sample. In our study we ran NMF using ranks 4-9 on the top 7000 genes in each sample. Hence each entry in Genes_nmf_w_basis is a matrix with 7000 rows (genes) X 39 columns (NMF programs)

Generate_Meta_Programs.R generates MPs from NMFs programs that were calculated for each sample using different ranks. The NMF programs were calculated per sample using the ‘NMF’ R package:
NMFs_per_sample = nmf(x = Expression_matrix, rank = 4:9, method="snmf/r", nrun = 10)
NMF programs are listed in Genes_nmf_w_basis, where each entry contains NMF gene-scores of a single sample.

1. "Using ranks 4-9 on the top 7000 genes in each sample"
   How to choose the top 7000 genes? Does this mean that the top 7000 for each rank are the same?

2. “NMF gene-scores”
   How to calculate the NMF gene-scores?

3.How to correlate cells with their corresponding MP? Do different MP correspond to different cell subtypes?

Generating MP_distributions error

I was able to download scalop successfully (see here https://stackoverflow.com/questions/76387189/fatal-error-relating-to-include-s-h-when-installing-r-scalop-package for help)

When i try to run the example data set My_study, I continuously get the error: Error in FUN(mat) : 'x' must be an array of at least two dimensions

anyone had any luck?

Install R package scalop failed

Hi, thank you for your wonderful work! I have learned a lot from this paper.
However, I have a small question. In ITH_hallmarks/MPs_distribution/MP_distribution.R, Line 23:
library(scalop) # see https://rdrr.io/github/jlaffy/scalop/man/sigScores.html
I have tried many ways, including:
remotes::install_github("jlaffy/scalop")
or downloaded .zip profile from github to install locally.
devtools::install_local("~/others/scalop-master/")
None did work, could you please tell me how to fix this problem? Thanks! Maybe just my Internet did not work.