ItLnc-BXE

This computational tool is designed for plant long non-coding RNA identification, and namely ItLnc-BXE ( 'Identification of plant lncRNAs using a Bagging-XGBoost-ensemble method with multiple features').

Datasets and tools we used are available at: https://pan.baidu.com/s/1M3zAve936BBbReoaFL8ZEQ

Setup

1.To use this tool, clone this repository on your machine by:

git clone https://github.com/BioMedicalBigDataMiningLab/ItLnc-BXE.git

2.Download datasets and tools
2.1 Download '/data' and '/feamodule.zip' from given url
2.2 Unzip feamodule.zip to /ItLnc-BXE/src/feamodule/
2.3 Unzip /ItLnc-BXE/src/feamodule/blast.zip to /ItLnc-BXE/src/feamodule/blast

Prerequisites

To use this tool you will need:

1. linux

2. python3

   • numpy
   • pandas
   • biopython
   • scikit-learn
   • xgboost
   • deap
   • CPAT

3. python2

   • numpy
   • regex
   • biopython
   • scikit-learn
   • scipy

4. nodejs

Example

Run:

python3 ItLnc-BXE.py -i input.fa -m a -o result

Model selection -m :
a : Arabidopsis_thaliana
c : Chlamydomonas_reinhardtii
h : Hordeum_vulgare
o : Oryza_sativa_Japonica_Group
p : Physcomitrella_patens
s : Solanum_tuberosum

Output files

all_features.csv: 175 features extracted from input transcripts.
result: the classes of predicted input trainscipts.