scvelo | RNA Velocity generalized through dynamical modeling | Genomics library

 by   theislab Python Version: 0.3.1 License: BSD-3-Clause

kandi X-RAY | scvelo Summary

kandi X-RAY | scvelo Summary

scvelo is a Python library typically used in Artificial Intelligence, Genomics applications. scvelo has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However scvelo build file is not available. You can install using 'pip install scvelo' or download it from GitHub, PyPI.

RNA Velocity generalized through dynamical modeling
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            kandi-support Support

              scvelo has a low active ecosystem.
              It has 334 star(s) with 89 fork(s). There are 14 watchers for this library.
              There were 2 major release(s) in the last 6 months.
              There are 58 open issues and 613 have been closed. On average issues are closed in 9 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of scvelo is 0.3.1

            kandi-Quality Quality

              scvelo has 0 bugs and 0 code smells.

            kandi-Security Security

              scvelo has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              scvelo code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              scvelo is licensed under the BSD-3-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              scvelo releases are available to install and integrate.
              Deployable package is available in PyPI.
              scvelo has no build file. You will be need to create the build yourself to build the component from source.
              scvelo saves you 6409 person hours of effort in developing the same functionality from scratch.
              It has 13703 lines of code, 488 functions and 66 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed scvelo and discovered the below as its top functions. This is intended to give you an instant insight into scvelo implemented functionality, and help decide if they suit your requirements.
            • Convert to a velocytoLoom
            • Filter genes
            • Filter and normalize data
            • Sum op
            • Plot the state likelihoods
            • Calculate the read and s
            • Calculate the variance of the distribution
            • Returns the distributions of the splicing potential
            • Compute cell origin fates
            • Get cell transition matrix
            • R Compute velocity genotypes
            • Compute cell fates
            • Rank genes by clustering
            • Plot the profiles on the grid
            • Set figure parameters
            • Calculate the velocity confidence interval
            • Clean up layers
            • Merge categorical groups
            • Fit regression recovery
            • Compute the least squares of x and y
            • Merge two datasets
            • Returns a pandas dataframe
            • Displays the proportions of each layer
            • Generate a simulation of splicing dynamics
            • R Compute the differential kinetic test
            • Plot a heatmap
            Get all kandi verified functions for this library.

            scvelo Key Features

            No Key Features are available at this moment for scvelo.

            scvelo Examples and Code Snippets

            No Code Snippets are available at this moment for scvelo.

            Community Discussions

            QUESTION

            subsetting anndata on basis of louvain clusters
            Asked 2020-Oct-13 at 08:40

            I want to subset anndata on basis of clusters, but i am not able to understand how to do it.

            I am running scVelo pipeline, and in that i ran tl.louvain function to cluster cells on basis of louvain. I got around 32 clusters, of which cluster 2 and 4 is of my interest, and i have to run the pipeline further on these clusters only. (Initially i had the loom file which i read in scVelo, so i have now the anndata.)

            I tried using adata.obs["louvain"] which gave me the cluster information, but i need to write a new anndata with only 2 clusters and process further.

            Please help on how to subset anndata. Any help is highly appreciated. (Being very new to it, i am finding it difficult to get)

            ...

            ANSWER

            Answered 2020-Oct-13 at 08:37

            If your adata.obs has a "louvain" column that I'd expect after running tl.louvain, you could do the subsetting as adata[adata.obs["louvain"] == "2"] if you want to obtain one cluster and adata[adata.obs['louvain'].isin(['2', '4'])] for obtaining cluster 2 & 4.

            Source https://stackoverflow.com/questions/63916137

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install scvelo

            You can install using 'pip install scvelo' or download it from GitHub, PyPI.
            You can use scvelo like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            Install
          • PyPI

            pip install scvelo

          • CLONE
          • HTTPS

            https://github.com/theislab/scvelo.git

          • CLI

            gh repo clone theislab/scvelo

          • sshUrl

            git@github.com:theislab/scvelo.git

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