Citable datasets (some associated with publications or preprints and some stand alone).
- Schnable (2019) Pan-Grass Syntenic Gene Set (sorghum referenced) with both maize v3 and maize v4 gene models figShare< doi: 10.6084/m9.figshare.7926674.v1
Updated syntenic gene list, now with
perl millet pearl millet, teff, and a way WAY better version of the oropetium genome. Please cite Zhang et al 2017.
Schnable JC (2018) Pan-Grass Syntenic Gene Set (sorghum referenced) with both maize v3 and maize v4 gene models figShare. 10.6084/m9.figshare.6974417.v1
Syntenic gene list for a bunch of species. Splits out maize1 and maize2 subgenomes. Uses maize v3, maizev4 sorghum v3, setaria v2.2 and rice v7 (among others). Constructed using LastZ to identify homologous genes, QuotaAlign to identify syntenic regions and python polishing scripts to identify high confidence orthologs within syntenic blocks. Maize v3 and maize v4 are treated as two separate species for the purposes of this analysis. Please cite Zhang et al 2017.
- Liang Z, Schnable JC. (2017) RGB and Hyperspectral images of approx. 1 meter tall corn plants from the genomes to fields inbred panel. Cyverse. 10.7946/P22K7V
A training dataset for developing methods for extracting new maize (corn) phenotypic measurements from different types of image data, testing the heritability of these measurements (the proportion of total variation explained by genetic differences), and searching for correlations between these measurements and agronomically relevant traits collected from the same genotypes in field trials across many states.
- Schnable JC, Zhang Y, Ngu DWC. (2016) Pan-Grass Syntenic Gene Set (sorghum referenced). figShare. 10.6084/m9.figshare.3113488.v1
Syntenic gene list for a bunch of species. Splits out maize1 and maize2 subgenomes. Uses maize v3, sorghum v3, setaria v2.2 and rice v7 (among others). Constructed using LastZ to identify homologous genes, QuotaAlign to identify syntenic regions and python polishing scripts to identify high confidence orthologs within syntenic blocks.
Schnable JC, Lyons E. (2015) Plant Paleopolyploidy. figShare. 10.6084/m9.figshare.1538627.v1
Best effort attempt to describe the positioning and evidence supporting different known whole genome events relative to the phylogeny of all plant genomes sequenced at the time. Also on CoGePedia.
- Schnable, JC (2015) Maize and Sorghum Genesets. figShare.
BED files answering the question: Where would each sorghum gene be in each maize subgenome if there were zero fractionation after the maize WGD? Also some useful figures generated using the same data.</li>
- Schnable JC. (2015) Sequenced Plant Genomes. CoGePedia Wiki Page
Exhaustive list of published plant genomes as of early 2015.
SLHTP - A set of software packages for automated image processing based phenotyping
Created by Alejandro D Pages, undergraduate researcher, 2018-19.
The Schnable Lab High Throughput Phenotyping (SLHTP) software package is written in python and houses the various scripts used in the development of three image processing software packages for automated phenotyping tasks. The tools available are:
- beanpheno A tool that can be used to process images of beans to obtain phenotype information for use in GWAS
- kernelpheno (incomplete) All the scripts and notebooks that were used in the development of a method to rate popcorn kernels for vitreousness from images taken on a light box. The image data was not collected with the intention of applying automated image processing methods in mind and therefore were too inconsistent for a simple method to be applied with good results. However progress was made towards that goal and perhaps a new data collection effort is warranted for the completion of this project.
- earpheno A set of tools that are useful for backend data management of a project involving PhytoMorph, a tool for extracting phenotype relevant measurements of maize ears.