seandavi / awesome-single-cell Goto Github PK

Great list, Sean and co. Would you be open to adding to this resource a list of people working on stats/computational methods in single-cell genomics/biology?

My reasons are somewhat selfish - I'm trying to organise a conference session and want a balanced female and male representation in my invitations. So I started compiling a list of women I'd love to see give a talk. I was thinking of sticking it somewhere online and hopefully getting community contributions and updates.

Please consider adding ACTIONet to the single cell package list:
https://www.nature.com/articles/s41467-020-18416-6

https://github.com/shmohammadi86/ACTIONet

Many thanks!

https://github.com/TaylorResearchLab/scedar

https://pypi.org/project/scedar/

https://journals.plos.org/ploscompbiol/article/comments?id=10.1371/journal.pcbi.1007794

1. A comparison of automatic cell identification methods for single-cell RNA sequencing data
   Article Link: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1795-z

2. Challenges in unsupervised clustering of single-cell RNA-seq data
   Article Link: https://www.nature.com/articles/s41576-018-0088-9

3. Tools for the analysis of high-dimensional single-cell RNA sequencing data
   Article Link: https://www.nature.com/articles/s41581-020-0262-0

@seandavi would you be interested in adding continuous integration to validate the URLs? If you're interested and enable Travis CI for this repository, I can make a pull request.

See an example here.

https://github.com/bm2-lab/mtSC

Hello I am doing single cell allelic analysis, main objective is to do transcriptional burst analysis, i have Choose SCALE which is using spike in for data normalization but the problem is I don't have the spike in information SCALE mentioned without normalization its not good to do SCALE. can you please suggest me any tools are method I can use your help will be appreciated

https://panglaodb.se/

pretty decent web tool + a python package adobo

https://oscar-franzen.github.io/adobo/

I suggest PHATE - Potential of Heat-diffusion for Affinity-based Transition Embedding - from the Krishnaswamy lab at Yale.

https://github.com/ChenMengjie/VIPER
https://github.com/ChenMengjie/Citrus

Here is another cell type identification and classification method (scCATCH). It is a cluster-based automatic annotation R package on cell types of clusters from single-cell RNA sequencing data. Please add it to your list, thanks!
https://github.com/ZJUFanLab/scCATCH

please add - Waddington Optimal Transport
Optimal-transport based software tools for single-cell RNA sequencing analysis

source - https://broadinstitute.github.io/wot/

https://pypi.org/project/scedar/

Published in PLoS Comp Bio earlier this year. https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007794

In the people part, Dana Pe'er has moved to MSKCC from Columbia University.

clustifyr is an RBI-authored packaged that classifies cells and clusters in single-cell RNA sequencing experiments using reference bulk RNA-seq data sets, sorted microarray expression data, single-cell gene signatures, or lists of marker genes.

Repo: https://github.com/rnabioco/clustifyr
Publication: https://f1000research.com/articles/9-223/v2

http://www.biorxiv.org/content/early/2017/05/24/141598

Thanks for putting together and maintaining this list, it's a great community resource!

I noticed that SCRAT is listed in the RNA-seq section when it's really ATAC-seq...or epigenomics in general. Would you consider changing the name of the "Methylation" section to Epigenomics and then add SCRAT (and some other new scATAC-seq tools) to this? Single-cell epigenomics seems to be an emerging field and there's probably a lot of tools that could go in this category.

On a related note, there also seems to be an emerging theme of tools that are particularily designed to merge disparate single-cell data types (for example "Matcher", listed in the Other section, for processing scRNA-seq and sc-"Epigenomics" (methylation or ATAC-seq). This seems like another section that could be brought out? Something like "Combining multiple data types"

Thanks for considering my suggestions.

Jon Sorenson

Dear Sean,

CHETAH has been published in Nucleic Acids Research, doi: 10.1093/nar/gkz543

Cheers,
Philip

https://github.com/smalikic/B-SCITE

https://bioconductor.org/packages/release/bioc/html/chromVAR.html

incredibly handy package

to my knowledge, there are. such as sergio, etc

Using Seurat for single cell analysis, there is problem:

pbmc <- FindClusters(object = pbmc, reduction.type = "pca", dims.use = 1:10,

•                  resolution = 0.6, print.output = 0, save.SNN = TRUE)
  

Error in file(file, "rt") : cannot open the connection
In addition: Warning messages:
1: running command 'java -jar "C:/Program Files/R/R-3.4.4/library/Seurat/java/ModularityOptimizer.jar" "C:\Users\huang\AppData\Local\Temp\RtmpuEbE34\file331c11c26286_edge_45021.txt" "C:\Users\huang\AppData\Local\Temp\RtmpuEbE34\file331c11c26286_output_45021.txt" 1 0.6 1 100 10 0 0' had status 127
2: In file(file, "rt") : cannot open file 'C:\Users\huang\AppData\Local\Temp\RtmpuEbE34\file331c11c26286_output_45021.txt': No such file or directory

How can I solve this problem?

Thank you!

• Compositional Perturbation Autoencoder (CPA): https://github.com/facebookresearch/CPA
• trVAE: https://github.com/theislab/trVAE
  • and its successor (?), scarches: https://github.com/theislab/scarches
    • https://scarches.readthedocs.io/en/latest/

cc @M0hammadL (cool talk at MIA today!)