The pipeline I developed is illustrated here:

There are 4 main folders where the scripts reside:

• genome_annotation
• orthologue_finder
• motif_prediction
• rnaseq_analysis

<Genome_annotation>

This folder has the scripts used for the de novo annotation of the genomes.

• "softmasking.irl.sh" Uses RepeatModeler and RepeatClassifier for masking genomes
• "braker_aw" Test script for braker2 developed by AnneW.
• "braker_irl_prot_and_rna.sh" modified version of anne's for running braker2 on proteins and RNAseq data.
• "busco.irl.sh" Code for running busco.
• "ncbi_dataset.py" Code for downloading bulk assemblies from ncbi.
• "softmasking.irl.sh" Code for softmasking genomes.

<orthologue_finder> This folder has the scripts used for the de novo annotation of the genomes.

• "rbb.irl.v1.2.sh" Reciprocal best blast for retreiving potential orthologues and their promoter sequences
• "rbb.irl.vprot3.sh"
• "rbb.irl.vprot4.sh"
• "rbb.process.sh"
• "iqtree"

<motif_prediction> This folder has some of the scripts used for analysing motif data.

<rnaseq_analysis> This folder has the scripts used for analyzing RNAseq data.

• "rnaseq_trim_fastqc.irl.v2.sh" Script for FASTQC and trimming RNAseq samples.
• "rnaseq_hisatindex.v2.sh" After running rnaseq_trim_fastqc.irl.v2.sh run this script to create a hisat index before aligning.
• "rnaseq_align_forbraker.irl.sh" Script for aligning RNAseq data and generate *.bam files for braker.
• "bamcoverage.irl.sh" File to visualize coverage from RNAseq data. This is useful when using a genome browser software to manually annotate genes.
• rnaseq_course_preprocess "Script from the RNASEQ course to FASTQC data for RNAseq analysis"
• rnaseq_course_preprocess_and_quantification.sh "Script from the RNASEQ course to FASTQC and quantification for RNAseq analysis"