Published March 9, 2020 | Version v1
Journal article Open

Identifying genetic variants underlying phenotypic variation in plants without complete genomes

  • 1. Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany

Description

Supplementary Dataset 1: A list of all phenotypes and top SNPs/k-mers passing their corresponding thresholds can be found here

Each phenotype has a separate directory which contains:
(1) original_phenotype_values.txt - the phenotypic values for each accession. For some of the A. thaliana’s phenotypes, the accession in the original work were marked not by their index, but with some other identifier. In these cases we had to find the accession’s index as explained in the method section. For the cases we could not find the index, the phenotypic value was not used, and will be missing from this file. 
(2) used_phenotype_values.txt - a subset of the original_phenotype_values.txt file. In this file we only include accessions for which we have sequencing data. This are the accessions we used for the GWAS analysis.

If the phenotype was not filtered out, the directory will contain additional 4 files:
3) kmers_pass_5percent_threshold_GEMMA_results.txt - The association results, as calculated by GEMMA, for all k-mers passing the 5% threshold.
4) kmers_pass_10percent_threshold_GEMMA_results.txt - The association results, as calculated by GEMMA, for all k-mers passing the 10% threshold.
5) snps_pass_5percent_threshold_GEMMA_results.txt - The association results, as calculated by GEMMA, for all SNPs passing the 5% threshold.
6) snps_pass_10percent_threshold_GEMMA_results.txt - The association results, as calculated by GEMMA, for all SNPs passing the 10% threshold.

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