Data from: Finding the right coverage: The impact of coverage and sequence quality on SNP genotyping error rates

Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in non-model organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction-enzyme-based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother-offspring dyads of Hoffman's two-toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference-aligned and de novo-assembled datasets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo-assembled datasets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference-aligned- and de novo-assembled datasets, respectively. Genotyping error rates declined to ≤0.01 in reference-aligned datasets with a coverage >30, but remained >0.04 in the de novo-assembled datasets. We observed approximately 10- and 13-fold declines in the number of loci sampled in the reference-aligned and de novo-assembled datasets when coverage was increased from >5 to >30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the tradeoff between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction-enzyme-based SNP studies. The data package contains two datasets: - Contains SAS script for estimating genotyping error rates using Mendelian incompatibilities. - Contains the SNP datasets used for analysis of genotyping error rates from reference alignment, reference alignment rxstacks, de novo assembly and de novo assembly rxstacks

A multi-model assessment of the early last deglaciation (PMIP4 LDv1)

This dataset includes surface air temperature (temp_mm_1_5m), Atlantic meridional overturning circulation streamfunction (merid_Atlantic_ym_dpth), mixed layer depth (mixLyrDpth; where used in the manuscript), sea ice concentration (iceconc_mm_srf; where used in the manuscript), and sea surface temperature (temp_mm_dpth_5) for 16 simulations of the last deglaciation from 9 different climate models (LOVECLIM, the 17th simulation, data can be found in a linked DOI). These simulations were collated as part of the Paleoclimate Modelling Intercomparison Project 4 Last Deglaciation version 1 (PMIP4 LDv1) for a multi-model intercomparison of the simulations for the early part of the last deglaciation (between 21 and 15 ka BP). For the purpose of the analysis, they were regridded on a 1 degree scale and ocean depths were standardized. The regridded files are included here, and the original grid is shown in Table 1 in the manuscript of the same name