Coder Social home page Coder Social logo

nlr-annotator's Introduction

NLR-Annotator version 2



  • Code rewritten
  • Integrated motif search tool. No dependency of MEME.

Introduction

NLR-Annotator is a tool to annotate loci associated with NLRs in large sequences. It is searching for amino acid motifs within all 6 frames of a nucleotide sequence. An NLR locus is defined from first to last motif that can be associated with an NLR.

It does NOT predict genes. A predicted NLR locus might be a pseudogene. If it is overlapping with a gene, the actual gene start or intron-exon boundaries are not given. It just points you to the loci that might be worth investigating, which we hope you will find useful. Details are published in Steuernagel et al.: The NLR-Annotator tool enables annotation of the intracellular immune receptor repertoire, Plant Physiology, 2020

JRE 1.6

Make sure you have the Java Runtime Environments 1.8 or higher. Download from http://java.com

Installation

JRE is installed. Download jar file from here

You will need two config files, mot.txt and store.txt.

Running NLR-Annotator

Run NLR-Annotator with java -jar NLR-Annotator-v2.0.jar -i input.fasta -x mot.txt -y store.txt -o output.txt

Replace "input.fasta" with the file (in fasta format) that contains the nucleotide sequences you want to annotate. If mot.txt and store.txt are not in your current directory, add the path.

If you use the -t parameter to run NLR-Annotator with multiple threads, please make sure the machine you are running it on has enough cores available.

In case you get an out-of-memory exception, add more to the java virtual machine, e.g. java -Xmx8000M -jar NLR-Annotator.jar ... will allow for 8000 MB.

All parameters

parameter argument description
-i input.fasta Input file in fasta format.
-o output.txt output file in tabular format
-g output.gff output file in gff format
-b output.bed output file in bed format
-m output.motifs.bed output file of the motifs in bed format
-a output.nbarkMotifAlignment.fasta output file of the nb-arc motifs as multiple alignment. This file can be used as input to generate a phylogenetic tree.
-f genome.fasta output.nlr.fasta flanking Write fasta of nlr loci. This parameter requires 3 arguments. The first is the original (not chopped) input sequence. The second is the file that is being generated. The third is the length of flanking sequence around the loci.
-t 1 number of threads
-n 1000 number of sequences per thread (default 1000)
-x mot.txt motif file, contains internal config setting for motifs
-y store.txt store file, contains internal config settings for motifs

Acknowledgements

Thanks to Jitender Cheema (JIC) for major code contribution to the Motif Search Engine!

nlr-annotator's People

Contributors

steuernb avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.