Gene expression profiling across ontogenetic stages in the wood white (Leptidea sinapis) reveals pathways linked to butterfly diapause regulation
Luis Leal, Venkat Talla, Thomas Källman, Magne Friberg, Christer Wiklund, Vlad Dincă, Roger Vila, and Niclas Backström. Molecular Ecology 27 (4), 935–48 (2018). https://doi.org/10.1111/mec.14501.
Luis Leal, Uppsala University, Uppsala, Sweden, 2017
- Filter libraries using TrimGalore
- Mask libraries using Fastq Masker
- Filter libraries using prinseq
- Filter libraries using condetri
- Screen libraries using fastQ Screen
- Reconcile paired-end libraries after using fastQ Screen (removes non-paired reads)
(Note: Index fasta files as required.)
01_quality_control.sh
(Note: Index fasta files as required.)
02_trinity_transcriptome_assembly.sh
- a. Annotate each trinity transcript using modified Trinotate protocol
03_trinotate_functional_annotation.sh
- b. Build local UniProt databases
04_build_local_UniProt_db.sh
- c. Find GO terms associated to each Trinity gene
05_associate_GO_terms_to_genes.sh
(Note: Index files as required.)
06_kallisto_transcript_quantification.sh
-
a. Convert counts-per-transcript to counts-per-gene using tximport
- a1. Associate Trinity transcript name to its gene name
07_associate_transcript_to_gene.py
- a2. Convert Kallisto output files from count-per-transcript to count-per-gene
08_tximport_aggregate_transcript_counts.R
-
b. Consolidate annotation file & gene counts
09_tximport_consolidateGenes.py
10_DESeq2.R
- a. Create two-column file that lists each Trinity gene and its associated GO terms
11_gene_to_GO.py
- b. Perform gene ontology enrichment analysis
12_TopGO.R