GeneMarkES-Sapelo2

Category

Bioinformatics

Program On

Sapelo2

Version

4.71

Author / Distributor

GeneMarkES

Description

"Gene Prediction in Eukaryotes. Novel genomes can be analyzed by the program GeneMark-ES utilizing unsupervised training." More details are at GeneMarkES

Running Program

Also refer to Running Jobs on Sapelo2

In order to use geneMarker you will need to download a key file and put it into your home directory. Please follow instructions as given below:

1) Go to http://exon.gatech.edu/GeneMark/license_download.cgi, fill the requested fields are read the license text. Note: you can select any tool and platform actually, e.g. GeneMark-ES/ET/EP+ ver 4.71_lic and LINUX64.

2) After pressing "I agree ..." button you will be redirected to a download page. You will need to download the 64bit key file only. The key file gm_key_64.gz will be downloaded to your local drive. Then please transfer it to the cluster using a transfer node. Please refer to Transferring Files.

3) The key file downloaded is in gzip format, on the cluster please unpack it (with gunzip) and move it to ~/.gm_key (the name should be exactly like this, with a dot in the beginning), for example:

gunzip gm_key_64.gz
mv gm_key_64 ~/.gm_key

where ~ is your home directory. i.e /home/MyID. Once the .gm_key file has been placed in your home dir you should be able to run GeneMarker.

Version 4.71

Version 4.71, installed at

• /apps/eb/GeneMark-ET/4.71-GCCcore-11.3.0/
• /apps/eb/GeneMark-ET/4.71-GCCcore-11.2.0/

To use it, please load the module with:

module load GeneMark-ET/4.71-GCCcore-11.3.0

or

module load GeneMark-ET/4.71-GCCcore-11.2.0

Here is an example of a shell script sub.sh to run it at the batch queue:

#!/bin/bash
#SBATCH --job-name=geneMarkJob
#SBATCH --partition=batch
#SBATCH --mail-type=ALL
#SBATCH --mail-user=username@uga.edu
#SBATCH --ntasks=1
#SBATCH --mem10gb
#SBATCH --time=08:00:00
#SBATCH --output=log.%j.out
#SBATCH --error=log.%j.err

cd $SLURM_SUBMIT_DIR

module load GeneMark-ET/4.71-GCCcore-11.3.0

gmes_petap.pl [options]

In the real submission script, at least all the above underlined values need to be reviewed or to be replaced by the proper values.

Here is an example of job submission command:

sbatch ./sub.sh 

Documentation

module load GeneMark-ET/4.71-GCCcore-11.3.0
gmes_petap.pl 

# -------------------
Usage:  /apps/eb/GeneMark-ET/4.71-GCCcore-11.3.0/gmes_petap.pl  [options]  --sequence [filename]

GeneMark-ES Suite version 4.71_lic
Suite includes GeneMark.hmm, GeneMark-ES, GeneMark-ET and GeneMark-EP algorithms.

Input sequence/s should be in FASTA format.

Select one of the gene prediction algorithms:

  To run GeneMark-ES self-training algorithm
    --ES

  To run GeneMark-ET with hints from transcriptome splice alignments
    --ET           [filename]; file with intron coordinates from RNA-Seq read splice alignment in GFF format
    --et_score     [number]; default 10; minimum score of intron in initiation of the ET algorithm

  To run GeneMark-EP with hints from protein splice alignments
    --EP           
    --dbep         [filename]; file with protein database in FASTA format
    --ep_score     [number,number]; default 4,0.25; minimum score of intron in initiation of the EP algorithm
    or
    --EP           [filename]; file with intron coordinates from protein splice alignment in GFF format

  To run GeneMark.hmm predictions using previously derived model
    --predict_with [filename]; file with species specific gene prediction parameters

  To run ES, ET or EP with branch point model. This option is most useful for fungal genomes
    --fungus

  To run hmm, ES, ET or EP in PLUS mode (prediction with hints)
    --evidence     [filename]; file with hints in GFF format

  To run algorithms with alternative genetic codes
    --gcode      [number]; default 1; supported 1 and 6/26

Output formatting options:
  --format       [label]; default GTF; output gene prediction in GTF of GFF3 format
  --work_dir     [folder name]; default current working directory .;

Masking option
  --soft_mask    [number] or [auto]; default auto; to indicate that lowercase letters stand for repeats;
                 algorithm hard masks only lowercase repeats longer than specified length
                 In 'auto' mode hard masking threshold is selected by algorithm based on the size of the input genome
  --mask_penalty [number] or [auto]; default 0.03;

Run options
  --cores        [number]; default 1; to run program with multiple threads
  --pbs          to run on cluster with PBS support
  --v            verbose

Optional sequence pre-processing parameters
  --max_contig   [number]; default 5000000; will split input genomic sequence into contigs shorter then max_contig
  --min_contig   [number]; default 50000 (10000 fungi); 
                 will ignore contigs shorter than min_contig in training 
  --max_gap      [number]; default 5000; will split sequence at gaps longer than max_gap
                 Letters 'n' and 'N' are interpreted as standing within gaps 
  --max_mask     [number]; default 5000; will split sequence at repeats longer then max_mask
                 Letters 'x' and 'X' are interpreted as results of hard masking of repeats

Optional parameters
  --max_intron            [number]; default 10000 (3000 fungi); maximum length of intron
  --max_intergenic        [number]; default 50000 (10000 fungi); maximum length of intergenic regions
  --min_contig_in_predict [number]; default 500; minimum allowed length of contig in prediction step
  --min_gene_in_predict   [number]; default 300 (120 fungi); minimum allowed gene length in prediction step
  --gc_donor              [value];  default 0.001; transition probability to GC donor in the range 0..1; 
                          'off' switches GC donor model OFF
  --gc3          [number]; GC3 cutoff in training for grasses

Developer options
  --training     to run only training step of algorithm; applicable to ES, ET or EP
  --prediction   to run only prediction step of algorithms using species parameters from previously executed training; applicable to ES, ET or EP
  --usr_cfg      [filename]; use custom configuration from this file
  --ini_mod      [filename]; use this file with parameters for algorithm initiation
  --key_bin
  --debug
# -------------------

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Installation

source code from GeneMarkES

System

64-bit Linux