Package: lantern 0.99.1

Yu Wang

lantern: Ancestry-Specific Rare Variant Association Analysis

Ancestry-specific rare variant burden testing for admixed populations. Splits genotype dosages by local ancestry (as inferred by 'RFMix') into per-ancestry dosages, using either phased haplotypes or unphased genotypes, where ambiguous mixed-ancestry heterozygotes are split with shrinkage toward 1/2, and writes them to 'SeqArray' GDS files. Ancestry-stratified gene-level tests are then run with the 'SMMAT' framework of Chen et al. (2019) <doi:10.1016/j.ajhg.2018.12.012> as implemented in 'GMMAT', and the per-ancestry p-values are combined with the Cauchy combination test of Liu and Xie (2020) <doi:10.1080/01621459.2018.1554485>.

Authors:Yu Wang [aut, cre], Bjoernar Tuftin [aut], Paul Auer [aut]

lantern_0.99.1.tar.gz
lantern_0.99.1.zip(r-4.7-x86_64)lantern_0.99.1.zip(r-4.7-arm64)lantern_0.99.1.zip(r-4.6-x86_64)lantern_0.99.1.zip(r-4.6-arm64)lantern_0.99.1.zip(r-4.5-x86_64)
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lantern_0.99.1.tar.gz(r-4.7-arm64)lantern_0.99.1.tar.gz(r-4.7-x86_64)lantern_0.99.1.tar.gz(r-4.6-arm64)lantern_0.99.1.tar.gz(r-4.6-x86_64)
lantern_0.99.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
lantern/json (API)

# Install 'lantern' in R:
install.packages('lantern', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yuw444/lantern/issues

Pkgdown/docs site:https://yuw444.github.io

On CRAN:

Conda:

softwaregeneticsgenomewideassociationsnpvariantannotation

4.62 score 19 scripts 12 exports 83 dependencies

Last updated from:aec0b2441c. Checks:1 NOTE, 15 OK. Indexed: yes.

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windows-release-x86_64OK206
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wasm-releaseOK130

Exports:ancestry_smmatancestry_splitancestry_split_dosageancestry_split_phasedcauchy_combineread_bed_filesplit_diploidsplit_diploid_multisplit_haplotypesplit_haplotype_multiwrite_ancestry_gdswrite_dosage_gds

Dependencies:backportsBiobaseBiocGenericsBiostringsbitbit64bootbroomclicliprcodetoolsCompQuadFormcpp11crayondata.tabledigestdplyrforcatsforeachformula.toolsgdsfmtgenericsGenomicRangesglmnetglueGMMATGWASExactHWhavenhmsIRangesiteratorsjomolatticelifecyclelme4logistfmagrittrMASSMatrixmgcvmiceminqamitmlnlmenloptrnnetnumDerivoperator.toolsordinalpanpillarpkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRcppArmadilloRcppEigenRdpackreadrreformulasrlangrpartS4VectorsSeqArraySeqinfoSeqVarToolsshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithrXVector

Split intuition: matrix examples for two and more populations
Overview | How the functions fit together | Part A: Two populations | A.1 Unphased split with split_diploid() | A.2 Phased split with split_haplotype() | Part B: More than two populations | B.1 Unphased split with split_diploid_multi() | B.2 Phased split with split_haplotype_multi() | B.3 Four or more populations | Part C: Shrinkage toward 1/2 | Session information
Rendered fromsplit-intuition.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-07-17

Toy example: splitting a VCF + MSP file (two and more populations)
Overview | Part A: Two populations | The input files | Splitting with phase (mode = "haplotype") | Splitting without phase (mode = "dosage") | Related functions | Part B: More than two populations (K = 4) | References | Session information
Rendered fromtoy-vcf-msp-example.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-07-17

Getting started with lantern
Introduction | Which haplotype carries the rare allele? | What the split gains | Workflow | Installation | Example data | Step 1: split dosages by local ancestry | Step 2: write per-ancestry GDS files | Step 3: test each gene in each ancestry | Further reading | References | Session information
Rendered fromlantern.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-06

Real data: chr19 association testing with binary, continuous, and count phenotypes
Overview | 1 Split and write the genotypes | 2 Gene groups and kinship | 3 Binary phenotype (family = binomial()) | 4 Continuous phenotype (family = gaussian()) | 5 Count phenotype (family = poisson()) | 6 Adjusting for covariates | 7 Testing every gene, with ancestry weights | 8 Other SMMAT tests and the raw SMMAT output | 9 More than two populations | 10 Gene-group files for your own data
Rendered fromreal-data-chr19.Rmdusingknitr::rmarkdown

Last update: 2026-10-26
Started: 2026-07-17