ensemblemerge's People
ensemblemerge's Issues
A simple scRNA-seq analysis pipeline
@dsouz072 Here is a very simple pipeline:
https://github.com/gongx030/ensemblemerge#1-a-simple-scrna-seq-pipeline
For each step, there exists several options but right now please run this simplest one and see how it goes. Thanks.
Add clustifyr for expression profile based annotation
BBKNN error on colab
params_merge <- new('BBKNNMerge', normalize = params_normalize)
x_merged <- Merge(x, params_merge) # x_merged is a Seurat object
have the following error:
Python package leidenalg must have version >= 0.8.8
Error in py_call_impl(callable, dots$args, dots$keywords): ValueError: X_pca does not have enough Dimensions. Provide a Representation with equal or more dimensions than`n_pcs` or lower `n_pcs`
Detailed traceback:
File "/usr/local/lib/python3.7/dist-packages/scanpy/tools/_umap.py", line 187, in umap
silent=True,
File "/usr/local/lib/python3.7/dist-packages/scanpy/tools/_utils.py", line 53, in _choose_representation
f'{use_rep} does not have enough Dimensions. Provide a '
Traceback:
1. Merge(x, params_merge)
2. Merge(x, params_merge)
3. sc$tl$umap(adata)
4. py_call_impl(callable, dots$args, dots$keywords)
Add scmap for annotation
Release of ensemblemerge v2.1.18
@dsouz072 Let us upgrade to this version for current the Etv2 scRNA-seq anaysis and the heartmap projects.
Add scMatch for annotation
Remove notebook dir
@dsouz072 This repo is a standard R package so non-standard directories such as notebook
is not allowed. Please remove it and move your notebooks to https://github.com/gongx030/ensemblemerge_project/blob/main/README.md. Thanks.
Implement an interface for dimension reduction without integration
Add scCCESS for clustering
https://github.com/PYangLab/scCCESS
This method has good performance in this benchmark study.
Add scPred for annotation
Unable to open notebooks in ReadMe table
I am unable to open the notebooks in this table as they are in a different repo and I don't think I have access to it.
Notebook not found
There was an error loading this notebook. Ensure that the file is accessible and try again.
https://github.com/gongx030/ensemblemerge_docs/blob/main/notebooks/normalization.ipynb
Thank you!
Add CIDR for clustering
Add classifyr for gene marker based annotation
Add support for Symphony
Paper: https://www.nature.com/articles/s41467-021-25957-x
R Package: https://github.com/immunogenomics/symphony
Add support for reference based integration including Symphony.
Add SCSA for annotation
Add support for Spectrum
Add DecontX for removing ambient RNAs
Add Seurat for reference based mapping
Add scArches for reference-based mapping
Paper: https://www.nature.com/articles/s41587-021-01001-7
Python package: https://scarches.readthedocs.io/en/latest/
Add SIMLR for clustering
Add support for scJoint
scJoint integrates atlas-scale single-cell RNA-seq and ATAC-seq data with transfer learning
Add Seurat for DE analysis
Add SingleCellNet for annotation
Make `BaseMerge` inheirts `BaseEmbed`
Add support for scLCA
Latent cellular analysis robustly reveals subtle diversity in large-scale single-cell RNA-seq data
https://pubmed.ncbi.nlm.nih.gov/31566233/
The tutorial / repo of scLCA can be found here: https://bitbucket.org/scLCA/single_cell_lca
Add class `UMAPEmbed' for UMAP embedding
scvi import error on colab
sprintf('pip install torch') %>% system()
sprintf('pip install scvi-tools==0.14.5') %>% system()
reticulate::import('scvi')
have the following error:
Error in py_module_import(module, convert = convert): ImportError: cannot import name '_CONSTANTS' from 'scvi._constants' (/usr/local/lib/python3.7/dist-packages/scvi/_constants.py)
Detailed traceback:
File "/usr/local/lib/R/site-library/reticulate/python/rpytools/loader.py", line 44, in _import_hook
level=level
File "/usr/local/lib/python3.7/dist-packages/scvi/__init__.py", line 6, in <module>
from ._constants import _CONSTANTS
Traceback:
1. reticulate::import("scvi")
2. py_module_import(module, convert = convert)
Installing github on Colab
I am getting an error while installing Ensemblemerge while using my personal authorization token
**Downloading GitHub repo gongx030/ensemblemerge@HEAD
Error: Failed to install 'ensemblemerge' from GitHub:
HTTP error 404.
Not Found
Did you spell the repo owner (`yulijia`) and repo name (`SIMLR`) correctly?
- If spelling is correct, check that you have the required permissions to access the repo.**
Traceback:
1. devtools::install_github("gongx030/ensemblemerge", auth_token = "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")
2. pkgbuild::with_build_tools({
. ellipsis::check_dots_used(action = getOption("devtools.ellipsis_action",
. rlang::warn))
. {
. remotes <- lapply(repo, github_remote, ref = ref, subdir = subdir,
. auth_token = auth_token, host = host)
. install_remotes(remotes, auth_token = auth_token, host = host,
. dependencies = dependencies, upgrade = upgrade, force = force,
. quiet = quiet, build = build, build_opts = build_opts,
. build_manual = build_manual, build_vignettes = build_vignettes,
. repos = repos, type = type, ...)
. }
. }, required = FALSE)
3. install_remotes(remotes, auth_token = auth_token, host = host,
. dependencies = dependencies, upgrade = upgrade, force = force,
. quiet = quiet, build = build, build_opts = build_opts, build_manual = build_manual,
. build_vignettes = build_vignettes, repos = repos, type = type,
. ...)
4. tryCatch(res[[i]] <- install_remote(remotes[[i]], ...), error = function(e) {
. stop(remote_install_error(remotes[[i]], e))
. })
5. tryCatchList(expr, classes, parentenv, handlers)
6. tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. value[[3L]](cond)
Error in Preprocess
I am following the same steps as mentioned in the documentation
library(ensemblemerge)
library(dplyr)
params_preprocess <- new('SeuratPreprocess', batch = 'batch')
so <- Preprocess(so, params_preprocess)
Error in Preprocess(so, params_preprocess): could not find function "Preprocess"
Is there another library that has the Preprocess function?
Implement an active assay slot for classes
Similar to the active assay slot in a Seurat object
Add support for SCINA
The tutorial can be found here: https://github.com/jcao89757/SCINA
Add SoupX for doublet detection
Add SC3 for clustering
Error while running ensemble merge using 'SeuratMerge'
Running command:
# integration
params_merge <- new('SeuratMerge', normalize = params_normalize)
x_merged <- Merge(x, params_merge) # x_merged is a Seurat object
Error:
Error in getGlobalsAndPackages(expr, envir = envir, globals = globals): The total size of the 7 globals exported for future expression (‘FUN()’) is 2.35 GiB.. This exceeds the maximum allowed size of 500.00 MiB (option 'future.globals.maxSize'). The three largest globals are ‘object.list’ (2.35 GiB of class ‘list’), ‘anchor.features’ (125.67 KiB of class ‘character’) and ‘FUN’ (35.52 KiB of class ‘function’)
Add DoubletFinder for doublet detection
Add scran's devolution strategy for normalization
Add MARS for de novo integration
Paper: https://www.nature.com/articles/s41592-020-00979-3
Python package: https://github.com/snap-stanford/mars
Add Scrublet for doublet detection
Add K-means clustering
Error while running PCAEmbed
code :
params_embed <- new('PCAEmbed', normalize = params_normalize)
so <- Embed(so, params_doubletdetect)
Error running Embed:
Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘Embed’ for signature ‘"Seurat", "DoubletFinderDoubletDetect"’
Traceback:
1. Embed(so, params_doubletdetect)
2. (function (classes, fdef, mtable)
. {
. methods <- .findInheritedMethods(classes, fdef, mtable)
. if (length(methods) == 1L)
. return(methods[[1L]])
. else if (length(methods) == 0L) {
. cnames <- paste0("\"", vapply(classes, as.character,
. ""), "\"", collapse = ", ")
. stop(gettextf("unable to find an inherited method for function %s for signature %s",
. sQuote(fdef@generic), sQuote(cnames)), domain = NA)
. }
. else stop("Internal error in finding inherited methods; didn't return a unique method",
. domain = NA)
. })(list(structure("Seurat", package = "SeuratObject"), structure("DoubletFinderDoubletDetect", package = "ensemblemerge")),
. new("standardGeneric", .Data = function (x, params, ...)
. standardGeneric("Embed"), generic = structure("Embed", package = "ensemblemerge"),
. package = "ensemblemerge", group = list(), valueClass = character(0),
. signature = c("x", "params"), default = NULL, skeleton = (function (x,
. params, ...)
. stop(gettextf("invalid call in method dispatch to '%s' (no default method)",
. "Embed"), domain = NA))(x, params, ...)), <environment>)
3. stop(gettextf("unable to find an inherited method for function %s for signature %s",
. sQuote(fdef@generic), sQuote(cnames)), domain = NA)
Add CHETAH for annotation
Add support for scCATCH
scCATCH: Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
Tutorial: https://raw.githack.com/ZJUFanLab/scCATCH/master/vignettes/tutorial.html
Add SingleR for annotation
Add Garnett for annotation
Paper: https://www.nature.com/articles/s41592-019-0535-3
Package: https://cole-trapnell-lab.github.io/garnett/docs/
Note: this tool may require a training step.
Add a `BaseNormalize` class and add support for sctransform
Add CellAssign/scMRMA for annotation
CellAssign:
Paper: https://www.nature.com/articles/s41592-019-0529-1
R package: https://github.com/Irrationone/cellassign
scMRMA:
Paper: https://academic.oup.com/nar/article/50/2/e7/6396893
R package: https://github.com/JiaLiVUMC/scMRMA
Add OnClass for annotation
Paper: https://www.nature.com/articles/s41467-021-25725-x
Python package: https://onclass.readthedocs.io/en/latest/
Add scDblFinder for doublet detection
Paper: Lun ATL (2018). Detecting doublet cells with scran. https://ltla.github.io/SingleCellThoughts/software/doublet_detection/bycell.html
R Package: https://rdrr.io/bioc/scran/man/doubletCells.html
Paper: https://f1000research.com/articles/10-979
R Package: https://bioconductor.org/packages/release/bioc/html/scDblFinder.html
Add CIDER for clustering
Paper: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02561-2
R Package: https://github.com/zhiyhu/CIDER
It is claimed that CIDER is able to address the batch effects when clustering cells.
Add Monocl3 for clustering
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