Last updated: 2020-10-09
Checks: 1 1
Knit directory: NaCRRI_2020GS/
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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 7efdd90 | wolfemd | 2020-10-09 | Build site. |
| html | c6022b6 | wolfemd | 2020-10-09 | Build site. |
| Rmd | 201e930 | wolfemd | 2020-10-09 | Start workflowr project. |
| html | fa3b6e1 | wolfemd | 2020-09-01 | Build site. |
| html | d97980a | wolfemd | 2020-09-01 | Build site. |
| Rmd | f3a0e16 | wolfemd | 2020-09-01 | Added a link to cassavabase FTP destination for the data. |
| html | d29d605 | wolfemd | 2020-09-01 | Build site. |
| Rmd | 6e27397 | wolfemd | 2020-09-01 | EMBRAPA C2 has been imputed. Publish report and share to cassavabase |
| html | ed70a5a | wolfemd | 2020-08-26 | Build site. |
| Rmd | 9d4dfab | wolfemd | 2020-08-26 | Code organized into functions. Ready to run imputation of C2? |
| Rmd | 4cc20db | wolfemd | 2020-08-26 | Start workflowr project. |
| Rmd | 245ee4f | wolfemd | 2020-08-26 | Start workflowr project. |
This repository and website documents all analyses, summary, tables and figures associated with NaCRRI genomic prediction and related procedures (e.g. imputation).
Imputation of the E. Africa reference panel and NaCRRI GS C2 (DArTseq only) was done in September 2019. The codes for 2019 imputation were never published in a Git repository, though they were shared internally. The 2019 imputed VCFs will serve as imputation reference panel for 2020. Therefore, I am publishing the 2019 codes here as is for reference.
“Imputation Reference Panel” consisted of 19,136 clones, includes samples in the W. Africa RefPanel except GS progeny. 413 clones (in addition to W. Africa dataset’s 411) were genotyped with both GBS and DArTseqLD (~340 from TARI). 56,250 SNP (imputed, phased and filtered). The East Africa version of the RefPanel was used to impute 1597 samples (NaCRRI GS C2) genotyped with DArTseq (not DArTseqLD). The resulting dataset after keeping only sites passing post-impute filters for the progeny has 23,431 SNP (“ready for GS”).
Found here: ftp://ftp.cassavabase.org/marnin_datasets/nextgenImputation2019/ImputationEastAfrica_StageIII_91119/
E.g. chr1_ImputationEastAfrica_AllSamples_ReadyForGP_91419.vcf.gz
Two DArT reports were involved:
DArT reports involved:
Steps:
Convert DCas19-4459 report to VCF for imputation: The report DCas19_4403 was converted to VCF and then included in the ImputationReferencePanel VCF and imputed along with the GBS/GBS+DArT samples.
Verify GBS-to-DArTseqLD sample matches: Verify GBS-2-DArT matches by PLINK IBD was done on samples DCas19_4459.
Imputation: this was a multi-stage process including assembly and filtering of VCFs, imputation with Beagle (4.1 and 5.0). The ultimate step of this pipeline was to impute the 1597 GS C2 progeny data, which were extracted from the DArTseq report “DCas19_4432”, with the imputation reference panel.
DArTseqLD (DCas20-5419) arrived in September 2020. From Robert Kawuki: From Robert Kawuki on Sep 1, 2020: “These samples were derived from Pre-breeding populations we have. On cassavabase under the NaCRRI folder these applies to populations namely”2019_SET_Pre_Breeding_Namulonge" and “2019_CET_Pre_Breeding_Namulonge”. These populations comprise crosses made between East African clones with Latin American and/or West African clones."
Steps:
Since imputation with Beagle5.0 is very fast, and given the origins of the samples, I’d like to impute it a few different ways and allow NaCRRI team to compare and contrast in downstream analysis.
Specifically, I think it makes sense to impute it with variants of the reference panel: (1) E. Africa ref panel, (2) L. America.
chr*_ImputationReferencePanel_StageVI_91119.vcf.gzchr*_DCas20_5419_EA_REFimputed.vcf.gzchr*_DCas20_5419_EA_REFimputedAndFiltered.vcf.gzDosageMatrix_DCas20_5419_EA_REFimputedAndFiltered.rdschr*_ImputationReferencePanel_EMBRAPA_Phased_102619.vcf.gzchr*_DCas20_5419_LA_REFimputed.vcf.gzchr*_DCas20_5419_LA_REFimputedAndFiltered.vcf.gzDosageMatrix_DCas20_5419_LA_REFimputedAndFiltered.rdsSUGGESTION: Use combination PCA, prediction, correlation of kinship matrices (off-diagonals and diagonals) to compare these datasets.
None as yet.
The R package workflowr was used to document this study reproducibly.
Much of the supporting data and output from the analyses documented here are too large for GitHub.
The repository will be mirrored, here: ftp://ftp.cassavabase.org/marnin_datasets/NaCRRI_2020GS/ with all data.
NOTICE: data/ and output/ are empty on GitHub. Please see ftp://ftp.cassavabase.org/marnin_datasets/NaCRRI_2020GS/ for access.
data/: raw data (e.g. unimputed SNP data)output/: outputs (e.g. imputed SNP data)analysis/: most code and workflow documented in .Rmd filesdocs/: compiled .html, “knitted” from .RmdSupporting functions code/
The analyses in the html / Rmd files referenced above often source R scripts in the code/ sub-folder.
The common strategy for imputation used across all imputations in 2019 is as follows:
Relies on:
Samples genotyping with both marker platforms (GBS + DArT)
SNP markers observed by both platforms
NextGenC custom DArT assay and reporting format, namely use of the ApeKI restriction enzyme _and_ reporting of read depth data to us.
Read depth data was used to compute genotype likelihoods (GL). For imputation, I used a combination of Beagle4.1 to do initial imputation steps. Beagle 4.1 is slow _but_ can use the GLs to produce a result which should be more accurate than simply using called genotypes (GT). For phasing steps _and_ for the imputation of target progeny (those with DArT-only), I used Beagle5.0 because it is _fast_ and _accurate_ IF you have GT calls and a big reference panel.
Be conservative. Between each imputation step, I applied the following filter: keep sites with AR2 or DR2>=0.75, P_HWE>1e-20, MAF>0.005. AR2 and DR2 are scores assigned by Beagle4.1 and Beagle5.0, respectively to measure expected quality of imputation (reported in the INFO field of VCF). P_HWE was based on HWE chi-square done by `vcftools`. MAF>0.005 is to remove anything that is essentially fixed in the dataset.
Samples that were supposed to have GBS and DArT were verified before combining the data. Used identity-by-descent (IBD) estimation in plink v1.9 (`plink1.9 –genome`) at DArT-GBS intersecting sites, to validate identity match (threshold >=0.75).
Two stages to building imputation reference panels:
Stage I. Impute all GBS+DArT samples. Plus GBS-only founders and diversity lines.
Stage II. Impute GBS-only GS descendents
Third and final Stage III: Impute target panels (i.e. selection candidates with DArT-only).