DoubletFinder | R package for detecting doublets

by chris-mcginnis-ucsf R Version: Current License: No License

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kandi X-RAY | DoubletFinder Summary

DoubletFinder is a R library. DoubletFinder has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

DoubletFinder can be broken up into 4 steps:. (1) Generate artificial doublets from existing scRNA-seq data. (2) Pre-process merged real-artificial data. (3) Perform PCA and use the PC distance matrix to find each cell's proportion of artificial k nearest neighbors (pANN). (4) Rank order and threshold pANN values according to the expected number of doublets.

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DoubletFinder has a low active ecosystem.

It has 231 star(s) with 60 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 16 open issues and 120 have been closed. On average issues are closed in 67 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DoubletFinder is current.

Quality

DoubletFinder has 0 bugs and 0 code smells.

Security

DoubletFinder has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

DoubletFinder code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DoubletFinder does not have a standard license declared.

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Without a license, all rights are reserved, and you cannot use the library in your applications.

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Installation instructions, examples and code snippets are available.

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DoubletFinder Key Features

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Community Discussions

Trending Discussions on DoubletFinder

Error in NormalizeData.default running DoubletFinder on an integrated seurat object in R

QUESTION

Error in NormalizeData.default running DoubletFinder on an integrated seurat object in R

Asked 2020-Jun-18 at 19:11

I'm trying to run DoubletFinder on a seurat object resulting from the integration of various datasets.

The Seurat object has 2 assays: RNA & integrated.

The integrated seurat object have been fully processed:

Normalization and FindVariableFeature pre-integration
ScaleData, RunPCA, FindNeighbors, FindClusters, RunUMAP on the integrated object.

The paramSweep_v3() function of DoubletFinder gives the following output:

...

ANSWER

Answered 2020-Jun-18 at 19:11

the DoubletFinder readme clearly states that you shouldn't run it on an aggregated dataset. It will produce false artificial doublets:

[https://github.com/chris-mcginnis-ucsf/DoubletFinder][1]

Do not apply DoubletFinder to aggregated scRNA-seq data representing multiple distinct samples (e.g., multiple 10X lanes). For example, if you run DoubletFinder on aggregated data representing WT and mutant cell lines sequenced across different 10X lanes, artificial doublets will be generated from WT and mutant cells, which cannot exist in your data. These artificial doublets will skew results. Notably, it is okay to run DoubletFinder on data generated by splitting a single sample across multiple 10X lanes.

I did it by reading in the individual samples, cluster them individually, run DoubletFinder, remove doublets and then run the integration workflow.

Source https://stackoverflow.com/questions/62266462

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