seandavi/awesome-single-cell

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

awesome-single-cell's Issues

Here are another two usefull tools in single-cell analyses

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

WOT

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

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

are there any python-based scRNAseq simulators?

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

Another Cell type identification and classification method

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

ChromVAR

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

incredibly handy package

Dana Pe'er moved to MSKCC

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

Add scImpute

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

Adding list of people (e.g., for talk invitations)

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.

Package scedar is missing.

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

PHATE

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

Add some probabilistic modeling approaches / libs

• 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!)

mtSC: Integrating multiple references for single cell assignment

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

Error in file(file, "rt") : cannot open the connection

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!

Single-cell package in Python to add to the list?

https://github.com/TaylorResearchLab/scedar

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

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

Supplement three review papers

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

cell type calling database panglao db

https://panglaodb.se/

pretty decent web tool + a python package adobo

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

adding separate section for ATAC-seq / combining methods?

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

Please consider adding ACTIONet to the single cell package list

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!

Continuous integration for links

@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.

Add clustifyr package?

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

Heres another one:

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

about allelic normalization or imputation

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

CHETAH is published in NAR

Dear Sean,

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

Cheers,
Philip