infercnvpy | Infer copy number variation from scRNA-seq data

 by   icbi-lab Python Version: 0.4.5 License: BSD-3-Clause

kandi X-RAY | infercnvpy Summary

kandi X-RAY | infercnvpy Summary

infercnvpy is a Python library. infercnvpy has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However infercnvpy build file is not available. You can install using 'pip install infercnvpy' or download it from GitHub, PyPI.

Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.
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            kandi-support Support

              infercnvpy has a low active ecosystem.
              It has 78 star(s) with 22 fork(s). There are 3 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 19 open issues and 23 have been closed. On average issues are closed in 40 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of infercnvpy is 0.4.5

            kandi-Quality Quality

              infercnvpy has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              infercnvpy 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

              infercnvpy releases are available to install and integrate.
              Deployable package is available in PyPI.
              infercnvpy has no build file. You will be need to create the build yourself to build the component from source.
              It has 1021 lines of code, 54 functions and 24 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed infercnvpy and discovered the below as its top functions. This is intended to give you an instant insight into infercnvpy implemented functionality, and help decide if they suit your requirements.
            • Infer the confidence interval of a given variable
            • Calculate running mean for each chromosome
            • Calculate the running mean
            • Sort a list
            • Ensure a is an array
            • Inner function
            • Get the reference for the given column
            • Read scevan data
            • Get chr positions from chr_pos_array
            • Compute the ith regular expression matrix
            • Choose MPX reponse
            • R Compute the TSNE
            • Calculate PCA
            • Parse the return section
            • Process return lines
            Get all kandi verified functions for this library.

            infercnvpy Key Features

            No Key Features are available at this moment for infercnvpy.

            infercnvpy Examples and Code Snippets

            No Code Snippets are available at this moment for infercnvpy.

            Community Discussions

            No Community Discussions are available at this moment for infercnvpy.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install infercnvpy

            You can install using 'pip install infercnvpy' or download it from GitHub, PyPI.
            You can use infercnvpy 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 infercnvpy

          • CLONE
          • HTTPS

            https://github.com/icbi-lab/infercnvpy.git

          • CLI

            gh repo clone icbi-lab/infercnvpy

          • sshUrl

            git@github.com:icbi-lab/infercnvpy.git

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