bx-python | manipulating biological data | Genomics library

by bxlab Python Version: 0.11.0 License: MIT

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

kandi X-RAY | bx-python Summary

bx-python is a Python library typically used in Artificial Intelligence, Genomics applications. bx-python has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install bx-python' or download it from GitHub, PyPI.

Tools for manipulating biological data, particularly multiple sequence alignments

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bx-python has a low active ecosystem.

It has 103 star(s) with 46 fork(s). There are 10 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 13 open issues and 35 have been closed. On average issues are closed in 344 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of bx-python is 0.11.0

Quality

bx-python has 0 bugs and 0 code smells.

Security

bx-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bx-python code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bx-python is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

bx-python releases are available to install and integrate.

Deployable package is available in PyPI.

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

bx-python saves you 10266 person hours of effort in developing the same functionality from scratch.

It has 20880 lines of code, 1560 functions and 223 files.

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

Top functions reviewed by kandi - BETA

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

Perform an interval on the source sequence
Get component by src
Return a new Alignment with only the components of the alignment
Add a component to the alignment
Create a feature reader from a gff file
Return the intersection of two sets
Convert bits to a list
Return the complement of a list of exons
Build the precedence precedence for operators
Compute the Lpaired correlation between two samples
Intersect two sets of bits
Parse a string or list of strings
Computes the score matrix based on alignment
Calculate coverage for each chromosome
Generator that parses a GFF file
Tiles a sequence of blocks into a single sequence
Subtract bitsets from a set of files
Iterate through all MAFs
Return component by src
Create a CDS reader from a GFF file
Create an instance from a pre - defined alignment
Build a scoring scheme from a string
Format the help string
Select motifs based on motif
Format the usage string
Return a list of extension modules
Collapse list of lists

Get all kandi verified functions for this library.

bx-python Key Features

No Key Features are available at this moment for bx-python.

bx-python Examples and Code Snippets

No Code Snippets are available at this moment for bx-python.

Community Discussions

Trending Discussions on bx-python

Interval intersection in pandas

QUESTION

Interval intersection in pandas

Asked 2019-Oct-29 at 12:15

Update 5:

This feature has been released as part of pandas 20.1 (on my birthday :] )

Update 4:

PR has been merged!

Update 3:

The PR has moved here

Update 2:

It seems like this question may have contributed to re-opening the PR for IntervalIndex in pandas.

Update:

I no longer have this problem, since I'm actually now querying for overlapping ranges from A and B, not points from B which fall within ranges in A, which is a full interval tree problem. I won't delete the question though, because I think it's still a valid question, and I don't have a good answer.

Problem statement

I have two dataframes.

In dataframe A, two of the integer columns taken together represent an interval.

In dataframe B, one integer column represents a position.

I'd like to do a sort of join, such that points are assigned to each interval they fall within.

Intervals are rarely but occasionally overlapping. If a point falls within that overlap, it should be assigned to both intervals. About half of points won't fall within an interval, but nearly every interval will have at least one point within its range.

What I've been thinking

I was initially going to dump my data out of pandas, and use intervaltree or banyan or maybe bx-python but then I came across this gist. It turns out that the ideas shoyer has in there never made it into pandas, but it got me thinking -- it might be possible to do this within pandas, and since I want this code to be as fast as python can possibly go, I'd rather not dump my data out of pandas until the very end. I also get the feeling that this is possible with bins and pandas cut function, but I'm a total newbie to pandas, so I could use some guidance! Thanks!

Notes

...

ANSWER

Answered 2017-May-09 at 23:22

This feature is was released as part of pandas 20.1

Source https://stackoverflow.com/questions/41983874

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

Vulnerabilities

No vulnerabilities reported

Install bx-python

You can install using 'pip install bx-python' or download it from GitHub, PyPI.
You can use bx-python 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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