geneview | Genomics data visualization in Python by using matplotlib | Data Visualization library

by ShujiaHuang Python Version: 0.2.1 License: GPL-3.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | geneview Summary

geneview is a Python library typically used in Analytics, Data Visualization applications. geneview has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install geneview' or download it from GitHub, PyPI.

geneview is a library for making attractive and informative genomic graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures. And now it is actively developed.

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Security

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Support

geneview has a low active ecosystem.

It has 46 star(s) with 8 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 1823 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of geneview is 0.2.1

Quality

geneview has 0 bugs and 0 code smells.

Security

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

geneview code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

geneview is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

geneview releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

geneview saves you 2095 person hours of effort in developing the same functionality from scratch.

It has 4597 lines of code, 281 functions and 49 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed geneview and discovered the below as its top functions. This is intended to give you an instant insight into geneview implemented functionality, and help decide if they suit your requirements.

Generate manhattan plot
Adjusts the text of the plot
Return a list of bounding boxes
Convert float to float
Plot a heatmap plot
Draw an adjacency plot
Compute a hierarchical clustrogram of data
Generate a colors palette
Vennx plot
Generate petal labels
Check if a dataset is already a venn dataset
Generate logics
Calculate the linkage matrix
Calculate linkage based on fastcluster method
Calculate linkage
Plot a qq plot
Generate a set of points
Plot a matplotlib plot
Draw ellipse
Return a less transparent color
Load a geneview dataset
Returns the path to the geneview data directory
Plot a qq norm
Sample a fastq file
Draws a triangle

Get all kandi verified functions for this library.

geneview Key Features

No Key Features are available at this moment for geneview.

geneview Examples and Code Snippets

geneview: A python package for genomics data visualization,Quick start,Manhattan

Python

Lines of Code : 76

License : Non-SPDX (NOASSERTION)

Copy

import matplotlib.pyplot as plt
import geneview as gv

# load data
df = gv.utils.load_dataset("gwas")
# Plot a basic manhattan plot with horizontal xtick labels and the figure will display in screen.
ax = gv.manhattanplot(data=df)
plt.show()

ax = ma

geneview: A python package for genomics data visualization,Quick start,Admixture plot

Python

Lines of Code : 27

License : Non-SPDX (NOASSERTION)

Copy

import matplotlib.pyplot as plt
from geneview.utils import load_dataset
from geneview import admixtureplot

f, ax = plt.subplots(1, 1, figsize=(14, 2), facecolor="w", constrained_layout=True, dpi=300)
admixtureplot(data=load_dataset("admixture_output

geneview: A python package for genomics data visualization,Quick start,Venn plots

Python

Lines of Code : 20

License : Non-SPDX (NOASSERTION)

Copy

import geneview as gv

table = {
    "Dataset 1": {"A", "B", "D", "E"},
    "Dataset 2": {"C", "F", "B", "G"},
    "Dataset 3": {"J", "C", "K"}
}
ax = gv.venn(table) 


from numpy.random import choice
import geneview as gv

dataset_dict = {
    name:

Community Discussions

Trending Discussions on geneview

Why can't simple web pages be displayed when used Django2.2?

QUESTION

Why can't simple web pages be displayed when used Django2.2?

Asked 2019-Apr-03 at 11:08

This is the error it reported：

...

ANSWER

Answered 2019-Apr-03 at 11:08

You are using class based view you just have to right template_name = 'index.html' to render a template

Source https://stackoverflow.com/questions/55489534

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

Vulnerabilities

No vulnerabilities reported

Install geneview

To install the released version, just do. This command will install geneview and all the dependencies.
We use a PLINK2.x association output data gwas.csv which is in geneview-data directory, as the input for the plots below. Here is the format preview of gwas:. The manhattanplot() function in geneview takes a data frame with columns containing the chromosomal name/id, chromosomal position, P-value and optionally the name of SNP(e.g. rsID in dbSNP). By default, manhattanplot() looks for column names corresponding to those outout by the plink2 association results, namely, #CHROM, POS, P, and ID, although different column names can be specificed by user. Calling manhattanplot() function with a data frame of GWAS results as the single argument draws a basic manhattan plot, defaulting to a darkblue and lightblue color scheme.
More tutorials about GWAS

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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