Skip to content

skbinfo/tncRNA-Toolkit

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

   _                    ______   _   _      _
 _| |_                 |  __  | | \ | |    / \
|_   _|  _____   ____  | |__| | |  \| |   /   \
  | |   |  _  | |  __| |  ____| | \ | |  / /_\ \
  | |_  | | | | | |__  | | \ \  | |\  | | |   | |
  |__ / |_| |_| |____| |_|  \_\ |_| \_| |_|   |_| Toolkit

tncRNA: tRNA derived non-coding RNAs

tncRNA Toolkit is a workflow to detect tRNA derived non-coding RNAs, viz. tRF-5s, tRF-3s, tRF-1, and tRNA halves. Input consists of genome fasta and single-end small RNA reads fastq file.

For more usage and output details, visit Manual page at "http://nipgr.ac.in/tncRNA/"

DOI


Dependencies:

  1. python3

Python modules: pandas (v1.1.0), biopython (v1.77)

Python module can be easily installed by following command:

pip3 install < module name > --user

  1. tRNAscan-SE (v2.0.6)

  2. samtools (v1.10)

  3. bedtools (v2.29.2)

[Note: python3, tRNAscan-SE, samtools, and bedtools are needed to be globaly installed or included it in the path.]

  1. Bowtie1 (v1.3.0)

  2. HAMR (v1.2)

[Note: bowtie1, and HAMR are already provided in tar package.]

Installation:

Download

git clone https://github.com/skbinfo/tncRNA-Toolkit.git

cd tncRNA-Toolkit/

Installing bowtie1:

cd util/

unzip bowtie-1.3.0-src.zip

cd bowtie-1.3.0-src/

make

cd ../

tar -xf HAMR-1.2.tar.gz

cd ../

[Note: 1. Bowtie and HAMR will be excuted from 'util' directory. You still need if you have already globaly installed. 2. HAMR-1.2 required python2 for running.]

Usage

First, create bowtie index for genome:

python3 tncRNAs.py -g < genome fasta > -s < species name >

It will automatically create the bowtie index alongwith needed files in "lib/indexes/< species name >"

Note:

Genome fasta header should be start with '>chr[Num]', for example >chr1, >chr2 so on. Mitochondrial and plastid fasta headers also should be as >chrMt & >chrPt respectively. This will be helpful for automation of scripts, and separation of nuclear & organellar region.

Once dealt with index build, user can further analyse the processed sRNA single-end data for that species.

tncRNAs prediction:

python3 tncRNAs.py -s < species name > -i < processed small RNA reads > -o < output dir >

Options Usage
-h print help
-s species name
-i small RNA reads (quality filtered and adapter trimmed) fastq (.fastq/.fq) file
-o output directory
Miscellaneous
-v mismatch or gap allowed [default: 0]. This option is for providing the integer value for -v option to the Bowtie aligner. It is recommended not to provide value >3.
-m limit to suppress all alignments if more than exist [default: 50]
-c cut-off value for read count [default: 10]
-t number of threads [default: 1]

If you have any questions, bug reports, or suggestions, please e-mail

Dr. Shailesh Kumar

Staff Scientist, Bioinformatics Laboratory #202

National Institute of Plant Genome Research (NIPGR), New Delhi

shailesh@nipgr.ac.in