Tangram | Spatial alignment of single cell transcriptomic data | Genomics library

by broadinstitute Jupyter Notebook Version: 1.0.4 License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Tangram Summary

Tangram is a Jupyter Notebook library typically used in Artificial Intelligence, Genomics applications. Tangram has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

To install Tangram, make sure you have PyTorch and scanpy installed. If you need more details on the dependences, look at the environment.yml file.

Support

Quality

Security

License

Reuse

Support

Tangram has a low active ecosystem.

It has 170 star(s) with 31 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 29 open issues and 34 have been closed. On average issues are closed in 43 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Tangram is 1.0.4

Quality

Tangram has no bugs reported.

Security

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

License

Tangram 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.

Reuse

Tangram releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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Tangram Key Features

No Key Features are available at this moment for Tangram.

Tangram Examples and Code Snippets

No Code Snippets are available at this moment for Tangram.

Community Discussions

Trending Discussions on Genomics

search for regex match between two files using python

Is there a way to permute inside using to variables in bash?

BigQuery Regex to extract string between two substrings

how to stop letter repeating itself python

Split multiallelic to biallelic in vcf by plink 1.9 and its variant name

Delete specific letter in a FASTA sequence

How to get the words within the first single quote in r using regex?

Does Apache Spark 3 support GPU usage for Spark RDDs?

Aggregating and summing columns across 1500 files by matching IDs in R (or bash)

Usage of compression IO functions in apache arrow

QUESTION

search for regex match between two files using python

Asked 2022-Apr-09 at 00:49

I´m working with two text files that look like this: File 1

...

ANSWER

Answered 2022-Apr-09 at 00:49

Perhaps you are after this?

Source https://stackoverflow.com/questions/71789818

QUESTION

Is there a way to permute inside using to variables in bash?

Asked 2021-Dec-09 at 23:50

I'm using the software plink2 (https://www.cog-genomics.org/plink/2.0/) and I'm trying to iterate over 3 variables.

This software admits an input file with .ped extention file and an exclude file with .txt extention which contains a list of names to be excluded from the input file.

The idea is to iterate over the input files and then over exclude files to generate single outputfiles.

Input files: Highland.ped - Midland.ped - Lowland.ped
Exclude-map files: HighlandMidland.txt - HighlandLowland.txt - MidlandLowland.txt
Output files: HighlandMidland - HighlandLowland - MidlandHighland - MidlandLowland - LowlandHighland - LowlandMidland

The general code is:

...

ANSWER

Answered 2021-Dec-09 at 23:50

Honestly, I think your current code is quite clear; but if you really want to write this as a loop, here's one possibility:

Source https://stackoverflow.com/questions/70298074

QUESTION

BigQuery Regex to extract string between two substrings

Asked 2021-Dec-09 at 01:11

From this example string:

...

ANSWER

Answered 2021-Dec-09 at 01:11

use regexp_extract(col, r"&q;Stockcode&q;:([^/$]*?),&q;.*")

if applied to sample data in your question - output is

Source https://stackoverflow.com/questions/70283253

QUESTION

how to stop letter repeating itself python

Asked 2021-Nov-25 at 18:33

I am making a code which takes in jumble word and returns a unjumbled word , the data.json contains a list and here take a word one-by-one and check if it contains all the characters of the word and later checking if the length is same , but the problem is when i enter a word as helol then the l is checked twice and giving me some other outputs including the main one(hello). i know why does it happen but i cant get a fix to it

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ANSWER

Answered 2021-Nov-25 at 18:33

As I understand it you are trying to identify all possible matches for the jumbled string in your list. You could sort the letters in the jumbled word and match the resulting list against sorted lists of the words in your data file.

Source https://stackoverflow.com/questions/70112201

QUESTION

Split multiallelic to biallelic in vcf by plink 1.9 and its variant name

Asked 2021-Nov-17 at 13:56

I am trying to use plink1.9 to split multiallelic into biallelic. The input is that

...

ANSWER

Answered 2021-Nov-17 at 09:45

I used bcftools to complete the task.

https://github.com/samtools/bcftools/issues/1193

Source https://stackoverflow.com/questions/70001737

QUESTION

Delete specific letter in a FASTA sequence

Asked 2021-Oct-12 at 21:00

I have a FASTA file that has about 300000 sequences but some of the sequences are like these

...

ANSWER

Answered 2021-Oct-12 at 20:28

You can match your non-X containing FASTA entries with the regex >.+\n[^X]+\n. This checks for a substring starting with > having a first line of anything (the FASTA header), which is followed by characters not containing an X until you reach a line break.

For example:

Source https://stackoverflow.com/questions/69545912

QUESTION

How to get the words within the first single quote in r using regex?

Asked 2021-Oct-04 at 22:27

For example, I have two strings:

...

ANSWER

Answered 2021-Oct-04 at 22:27

For your example your pattern would be:

Source https://stackoverflow.com/questions/69442717

QUESTION

Does Apache Spark 3 support GPU usage for Spark RDDs?

Asked 2021-Sep-23 at 05:53

I am currently trying to run genomic analyses pipelines using Hail(library for genomics analyses written in python and Scala). Recently, Apache Spark 3 was released and it supported GPU usage.

I tried spark-rapids library start an on-premise slurm cluster with gpu nodes. I was able to initialise the cluster. However, when I tried running hail tasks, the executors keep getting killed.

On querying in Hail forum, I got the response that

That’s a GPU code generator for Spark-SQL, and Hail doesn’t use any Spark-SQL interfaces, only the RDD interfaces.

So, does Spark3 not support GPU usage for RDD interfaces?

...

ANSWER

Answered 2021-Sep-23 at 05:53

As of now, spark-rapids doesn't support GPU usage for RDD interfaces.

Source: Link

Apache Spark 3.0+ lets users provide a plugin that can replace the backend for SQL and DataFrame operations. This requires no API changes from the user. The plugin will replace SQL operations it supports with GPU accelerated versions. If an operation is not supported it will fall back to using the Spark CPU version. Note that the plugin cannot accelerate operations that manipulate RDDs directly.

Here, an answer from spark-rapids team

Source: Link

We do not support running the RDD API on GPUs at this time. We only support the SQL/Dataframe API, and even then only a subset of the operators. This is because we are translating individual Catalyst operators into GPU enabled equivalent operators. I would love to be able to support the RDD API, but that would require us to be able to take arbitrary java, scala, and python code and run it on the GPU. We are investigating ways to try to accomplish some of this, but right now it is very difficult to do. That is especially true for libraries like Hail, which use python as an API, but the data analysis is done in C/C++.

Source https://stackoverflow.com/questions/69273205

QUESTION

Aggregating and summing columns across 1500 files by matching IDs in R (or bash)

Asked 2021-Sep-07 at 13:09

I have 1500 files with the same format (the .scount file format from PLINK2 https://www.cog-genomics.org/plink/2.0/formats#scount), an example is below:

...

ANSWER

Answered 2021-Sep-07 at 11:10

a tidyverse solution

Source https://stackoverflow.com/questions/69086946

QUESTION

Usage of compression IO functions in apache arrow

Asked 2021-Jun-02 at 18:58

I have been implementing a suite of RecordBatchReaders for a genomics toolset. The standard unit of work is a RecordBatch. I ended up implementing a lot of my own compression and IO tools instead of using the existing utilities in the arrow cpp platform because I was confused about them. Are there any clear examples of using the existing compression and file IO utilities to simply get a file stream that inflates standard zlib data? Also, an object diagram for the cpp platform would be helpful in ramping up.

...

ANSWER

Answered 2021-Jun-02 at 18:58

Here is an example program that inflates a compressed zlib file and reads it as CSV.

Source https://stackoverflow.com/questions/67799265

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

Vulnerabilities

No vulnerabilities reported

Install Tangram

To install Tangram, make sure you have PyTorch and scanpy installed. If you need more details on the dependences, look at the environment.yml file.
set up conda environment for Tangram
install tangram-sc from shell:
To start using Tangram, import tangram in your jupyter notebooks or/and scripts

Support

Mapping with cluster mode is fine on a standard laptop. For mapping at single cell level, GPU is not required but is recommended. We run most of our mappings on a single P100 which maps ~50k cells in a few minutes. A good way to start is to use the top 1k unique marker genes, stratified across cell types, as training genes. Alternatively, you can map using the whole transcriptome. Ideally, training genes should contain high quality signals: if most training genes are rich in dropouts or obtained with bad RNA probes your mapping will not be accurate. You do not need to segment cells in your histology for mapping on spatial transcriptomics data (including Visium and Slide-seq). You need, however, cell segmentation if you wish to deconvolve the data (ie deterministically assign a single cell profile to each cell within a spatial voxel). Reduce your spatial data in various parts and map each single part. If that is not sufficient, you will need to downsample your single cell data as well.

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