TGIRT-HAMR stands for thermostable group II intron reverse transcriptase (TGIRT) high-throughput annotation of modification using RNA-seq. This software adopted the algorithm in HAMR for predicting post-transcriptional modifications in TGIRT.
INSTALL:
git clone https://github.com/wckdouglas/tgirt-hamr.git
cd tgirt-hamr
make
Run:
python $(tgirt-hamr-path)/script/tgirt-hamr.py
usage: python tgirt-hamr.py [options] -e <TGIRT> -i <input bam> -o <output bed> -r <reference fasta>
[options]
-e, --enzyme=<gsi>|<tei> This can be <gsi> or <tei> for GsI-IIc and TeI4c libraries respectively
-i, --inBam=<bamfile> input bam file
-o, --outBed=<bedfile> output bed file
-r, --refFasta=<fasta file> reference fasta file
-p, --cores=<int> number of cores to use default: 1
-y, --hyp=<hyp1>|<hyp2> hypothesis to use, can be <hyp1> or <hyp2> default: hyp2
-s, --seqErr=<float> sequencing error probability default: 0.01
-t, --pThreshold=<float> False discovery rate cut off default: 0.01
-m, --model=<knn> model for prediction, can be anything available in R::caret default: knn
-q, --qual=<int> base quality cut off for retaining bases from read default: 33
-c, --cov=<int> coverage cutoff for position to retain default: 10
-h, --help print out usage
Dependencies:
softwares: R >=3.1.0, python = 2.7, samtools >= 1.2, gcc > 4.4.5
R-package: dplyr, caret, readr, stringr, tidyr, Rcpp, getopt, doMC, tgirthamr