ngsplot | Quick mining and visualization of NGS data | Genomics library
kandi X-RAY | ngsplot Summary
kandi X-RAY | ngsplot Summary
DNA sequencing is at the core of genomics. The NGS technology has been tremendously improved in the past few years. It can now determine more than a billion DNA sequences within a week, generating terabytes of data. Applications include but are not limited to: 1. ChIP-seq which profiles genome-wide protein-DNA interactions; 2. RNA-seq which measures the gene expression levels. It is very helpful to look at the enrichment of those sequences at various functional regions. Although a genome browser (such as the UCSC genome browser) allows a researcher to visualize these data, it limits the view to a slice of the genome, while the genome is like a huge collection of functional elements that can be classified into different categories; each category of elements may perform distinct functions and they might contain sub-modules. The signature advantage of ngs.plot is that it collects a large database of functional elements for many genomes. A user can ask for a functionally important region to be displayed in one command. It handles large sequencing data efficiently and has only modest memory requirement. For example, ngs.plot was used to draw a plot for all the genes on the mouse genome from 71GB of ChIP-seq data in 25 min, with a memory footprint of 2.7GB using 4 x 2.4GHz CPU cores. ngs.plot is also easy to use. A user only needs to create a very small text file called configuration, telling the program which samples to look at and how they should be combined with different regions, and then run the program with one command. A web-based version (integrated into Galaxy) is also available for the ones who are "allergic" to terminals.
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ngsplot Key Features
ngsplot Examples and Code Snippets
Community Discussions
Trending Discussions on Genomics
QUESTION
I´m working with two text files that look like this: File 1
...ANSWER
Answered 2022-Apr-09 at 00:49Perhaps you are after this?
QUESTION
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 23:50Honestly, I think your current code is quite clear; but if you really want to write this as a loop, here's one possibility:
QUESTION
From this example string:
...ANSWER
Answered 2021-Dec-09 at 01:11use regexp_extract(col, r"&q;Stockcode&q;:([^/$]*?),&q;.*")
if applied to sample data in your question - output is
QUESTION
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
...ANSWER
Answered 2021-Nov-25 at 18:33As 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.
QUESTION
I am trying to use plink1.9 to split multiallelic into biallelic. The input is that
...ANSWER
Answered 2021-Nov-17 at 09:45I used bcftools to complete the task.
QUESTION
I have a FASTA file that has about 300000 sequences but some of the sequences are like these
...ANSWER
Answered 2021-Oct-12 at 20:28You 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:
QUESTION
For example, I have two strings:
...ANSWER
Answered 2021-Oct-04 at 22:27For your example your pattern would be:
QUESTION
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 05:53As 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++.
QUESTION
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 11:10a tidyverse solution
QUESTION
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 18:58Here is an example program that inflates a compressed zlib file and reads it as CSV.
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Install ngsplot
You need R version >= 2.15.0 and Python 2.7 to be able to use ngs.plot. Please also update related R and Bioconductor packages to the corresponding version.
Download the ngs.plot package to a desired folder, such as ~/software, and extract it: cd ~/software tar xzvf ngsplot-XXX.tar.gz The program will be extracted into a folder called "ngsplot".
Add ngsplot executables to your PATH. Under bash, add line like this: export PATH=~/software/ngsplot/bin:$PATH to your ~/.bash_profile
Set environment variable NGSPLOT like this in your ~/.bash_profile: export NGSPLOT=~/software/ngsplot Then in the terminal, execute: source ~/.bash_profile A trick to avoid setting environment variable is: NGSPLOT=/your/path/to/ngsplot bash -c 'ngs.plot.r XXX'
Install some required libraries in R: install.packages("doMC", dep=T) install.packages("caTools", dep=T) install.packages("utils", dep=T) For R 3.0+, utils is no longer needed. For R <3.0, you probably already have caTools and utils installed but it does not hurt to check. Then execute in R: source("http://bioconductor.org/biocLite.R") biocLite( "BSgenome" ) biocLite( "Rsamtools" ) biocLite( "ShortRead" )
(Optional) Install ngsplot package in Galaxy: read the galaxy/README.txt for instructions. A wiki will be provided to demonstrate the workflow of ngs.plot in Galaxy.
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