NAIBR | Novel Adjacency Identification with Barcoded Reads

by raphael-group Python Version: Current License: MIT

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

kandi X-RAY | NAIBR Summary

NAIBR is a Python library typically used in Healthcare, Pharma, Life Sciences applications. NAIBR has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However NAIBR build file is not available. You can download it from GitHub.

NAIBR (Novel Adjacency Identification with Barcoded Reads) identifies novel adjacencies created by structural variation events such as deletions, duplications, inversions, and complex rearrangements using linked-read whole-genome sequencing data produced by 10X Genomics. Please refer to the publication for details about the method. NAIBR takes as in put a BAM file produced by 10X Genomic's Long Ranger pipeline and outputs a BEDPE file containing predicted novel adjacencies and a likelihood score for each adjacency.

Support

Quality

Security

License

Reuse

Support

NAIBR has a low active ecosystem.

It has 12 star(s) with 6 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 13 open issues and 5 have been closed. On average issues are closed in 60 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of NAIBR is current.

Quality

NAIBR has 0 bugs and 0 code smells.

Security

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

NAIBR code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NAIBR 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

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

NAIBR has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 1145 lines of code, 80 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Estimate the lmin distance from the reads
Calculate the candidates that overlap the given reads
Calculate the length distribution for each chromosome
Calculates the length distribution given a list of LRs
Fit the model to data
Find the indices of the largest overlap in a list
Add split information
Get the orientation of a read
Run NAs for a given chromosome
Make a dictionary containing all the candidates for a given chromosome
Calculate the candidates for the given reads
Predict NAs for each candidate
Add a disc
Get all CSMs from the candidates
Get the CSMs for a candidate
Get the CSMs for the given branch
Return a list of discards for a given candidate
Compute the score for a single candidate pair
Score a CSM
Compute the probability of mapq
Computes the mismap probability of a sequence
Predict NAs
Run a function on input_list
Run NAs on a candidate
Make a dictionary of candidates for a candidate
Write scores to a BED file
Logarithm of x

Get all kandi verified functions for this library.

NAIBR Key Features

No Key Features are available at this moment for NAIBR.

NAIBR Examples and Code Snippets

No Code Snippets are available at this moment for NAIBR.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install NAIBR

You can download it from GitHub.
You can use NAIBR 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 .

Find more information at: