HLA-LA | Fast HLA type inference from whole-genome data | Data Labeling library

by DiltheyLab C++ Version: v1.0.3 License: GPL-3.0

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

kandi X-RAY | HLA-LA Summary

HLA-LA is a C++ library typically used in Artificial Intelligence, Data Labeling applications. HLA-LA has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Fast HLA type inference from whole-genome data

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Quality

Security

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Reuse

Support

HLA-LA has a low active ecosystem.

It has 101 star(s) with 35 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 53 open issues and 39 have been closed. On average issues are closed in 145 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of HLA-LA is v1.0.3

Quality

HLA-LA has 0 bugs and 0 code smells.

Security

HLA-LA has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

HLA-LA code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

HLA-LA 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

HLA-LA releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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HLA-LA Key Features

No Key Features are available at this moment for HLA-LA.

HLA-LA Examples and Code Snippets

No Code Snippets are available at this moment for HLA-LA.

Community Discussions

Trending Discussions on Data Labeling

How can I do this split process in Python?

Replacing a character with a space and dividing the string into two words in R

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

QUESTION

How can I do this split process in Python?

Asked 2021-Dec-30 at 14:06

I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

What I've done so far is make this representation with the same enumerator class.

A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

...

ANSWER

Answered 2021-Dec-30 at 13:57

Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

Source https://stackoverflow.com/questions/70532286

QUESTION

Replacing a character with a space and dividing the string into two words in R

Asked 2020-Nov-18 at 07:32

I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

i have this:

...

ANSWER

Answered 2020-Nov-16 at 07:24

Try something like:

Source https://stackoverflow.com/questions/64853962

QUESTION

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

Asked 2020-Oct-28 at 20:31

Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

...

ANSWER

Answered 2020-Oct-27 at 22:39

Is the data behind virtual network by any chance?

Source https://stackoverflow.com/questions/64546521

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

Vulnerabilities

No vulnerabilities reported

Install HLA-LA

g++ with support for C++11 (e.g. 4.7.2) Boost >= 1.59 Bamtools (now tested with 2.5.1 -- the makefile also contains instructions for older versions) libz. bwa >= 0.7.12 samtools >= 1.3 picard.
For Boost: if you specified /path/to/boost as BOOST_PATH (either via the command line or directly in the makefile), the paths /path/to/boost/include and /path/to/boost/lib should exist on your system. Furthermore, /path/to/boost/lib should contain the required library files (boost_system, boost_filesystem, boost_random, boost_serialization); on a standard Linux, this would typically translate into the presence of lib + name + .a files in this folder (e.g.: for library boost_system, on a standard Linux there should be a libboost_system.a file).
For bamtools: if you specified /path/to/bamtools/ as BAMTOOLS_PATH (either via the command line or directly in the makefile), the paths /path/to/bamtools/include/bamtools, /path/to/bamtools/src and /path/to/bamtools/lib64 should exist on your system. If /path/to/bamtools/lib64 does NOT exist on your system, but /path/to/bamtools/lib does, edit line 11 of the makefile accordingly. Furthermore, the specified bamtools library directory (either /path/to/bamtools/lib64 or /path/to/bamtools/lib) should contain a bamtools library file. On most Linux machines, this is equivalent to there being a libbamtools.a file.
Download and index the "NA12878 mini" test CRAM file from https://www.dropbox.com/s/xr99u3vqaimk4vo/NA12878.mini.cram?dl=0 (md5sum 45d1769ffed71418571c9a2414465a12; 316M), rename the file to remove the dl=0 suffix (mv NA12878.mini.cram?dl=0 NA12878.mini.cram), run HLA*LA (see below), and compare the output with https://github.com/DiltheyLab/HLA-LA/blob/master/NA12878_example_output_G.txt. All allele calls should agree, and Q should be 1 for all calls.
If you want to create a central installation of HLA-LA, you will probably want to delete the workingDir entry from the paths.ini file -- this forces users to specify a working directory via the command line and avoids shared access to the same working directory.

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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