Data
We receive support from the Australian Biocommons Apollo project and have used this to create genome browsers for new genomes generated by our group.
- Genome browsers for complete genomes are available at https://coral.genome.edu.au
- Pareledone turqueti partial genome: reference sequence
Reproducible analysis for publications
We work with large genomic, transcriptomic and proteomic data, often combining outputs from multiple analyses to generate inferences. A typical project will involve many small shell scripts, some command-line tools written in Python and lots of R code. We use github to manage this complexity, collaborate and share our work. For new projects we suggest starting with our project template.
Examples of publications with associated code repositories:
- Evolutionary responses of a reef-building coral to climate change at the end of the last glacial maximum
- Genomic signatures in the coral holobiont reveal host adaptations driven by Holocene climate change and reef specific symbionts.
- Shotgun Proteomics Analysis of Saliva and Salivary Gland Tissue from the Common Octopus Octopus vulgaris
- Comparative Proteomic Analysis of Slime from the Striped Pyjama Squid, Sepioloidea lineolata, and the Southern Bottletail Squid, Sepiadarium austrinum (Cephalopoda: Sepiadariidae)
Nextflow pipelines
We are developing a set of pipelines in nextflow to automate core analysis tasks encountered in marine omics projects. The goal of these pipelines is to automate common processes and provide a form of working documentation representing current best-practices in the lab. Working pipelines currently include;
- movp : Marine Omics Variant calling Pipeline. Calls SNPs and small indels from short-reads
- moqc : Marine Omics Quality Control pipeline. Uses fastqc to report on read data quality and kraken to report on taxonomic composition (eg to detect contaminants).
- morp : Marine Omics RNAseq Pipeline. Maps reads to a transcriptome and quantifies transcript abundance using RSEM
- moat : Marine Omics AnnoTation pipeline. Functional annotation on a set of predicted proteins.
- mod2s: Marine Omics DS2 Pipeline. kmer-based sample clustering
Getting setup to run these pipelines can be a little challenging. To make things easier we have produced a guide to using marine omics pipelines
Software
- ampir: Antimicrobial peptide prediction in R by Legana Fingerhut