EVidenceModeler 1.1.1-GCCcore-8.3.0

The EVidenceModeler (aka EVM) software combines ab intio gene predictions and protein and transcript alignments into weighted consensus gene structures. EVM provides a flexible and intuitive framework for combining diverse evidence types into a single automated gene structure annotation system. Inputs to EVM include the genome sequence, gene predictions and alignment data in GFF3 format, and a list of numeric weight values to be applied to each type of evidence. The weights can be configured manually.

Accessing EVidenceModeler 1.1.1-GCCcore-8.3.0

To load the module for EVidenceModeler 1.1.1-GCCcore-8.3.0 please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load EVidenceModeler/1.1.1-GCCcore-8.3.0

BEAR Apps Version

2019b

Architectures

EL8-cascadelake — EL8-icelake — EL8-sapphirerapids

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

More Information

For more information visit the EVidenceModeler website.

Dependencies

This version of EVidenceModeler has a direct dependency on: GCCcore/8.3.0 Perl/5.30.0-GCCcore-8.3.0

Required By

This version of EVidenceModeler is a direct dependent of: funannotate/1.8.1-foss-2019b-Python-2.7.16 funannotate/1.8.1-foss-2019b-Python-3.7.4

Last modified on 12th October 2020