Package: MICSQTL 1.10.0

Qian Li

MICSQTL: MICSQTL (Multi-omic deconvolution, Integration and Cell-type-specific Quantitative Trait Loci)

Our pipeline, MICSQTL, utilizes scRNA-seq reference and bulk transcriptomes to estimate cellular composition in the matched bulk proteomes. The expression of genes and proteins at either bulk level or cell type level can be integrated by Angle-based Joint and Individual Variation Explained (AJIVE) framework. Meanwhile, MICSQTL can perform cell-type-specic quantitative trait loci (QTL) mapping to proteins or transcripts based on the input of bulk expression data and the estimated cellular composition per molecule type, without the need for single cell sequencing. We use matched transcriptome-proteome from human brain frontal cortex tissue samples to demonstrate the input and output of our tool.

Authors:Yue Pan [aut], Qian Li [aut, cre], Iain Carmichael [ctb]

MICSQTL_1.10.0.tar.gz
MICSQTL_1.10.0.zip(r-4.7)MICSQTL_1.10.0.zip(r-4.6)MICSQTL_1.10.0.zip(r-4.5)
MICSQTL_1.10.0.tgz(r-4.6-any)MICSQTL_1.10.0.tgz(r-4.5-any)
MICSQTL_1.10.0.tar.gz(r-4.7-any)MICSQTL_1.10.0.tar.gz(r-4.6-any)
MICSQTL_1.10.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MICSQTL/json (API)
NEWS

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

Bug tracker:https://github.com/yuepan027/micsqtl/issues

Datasets:
  • se - Example data

On BioConductor:MICSQTL-1.11.0(bioc 3.24)MICSQTL-1.10.0(bioc 3.23)

geneexpressiongeneticsproteomicsrnaseqsequencingsinglecellsoftwarevisualizationcellbasedassayscoverage

4.00 score 6 scripts 292 downloads 4 exports 156 dependencies

Last updated from:8a615ba256 (on RELEASE_3_23). Checks:1 NOTE, 9 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksNOTE220
linux-devel-x86_64OK499
source / vignettesOK316
linux-release-x86_64OK403
macos-release-arm64OK350
macos-oldrel-arm64OK371
windows-develOK570
windows-releaseOK589
windows-oldrelOK544
wasm-releaseOK175

Exports:ajive_decompcsQTLdeconvfeature_filter

Dependencies:abindannotateAnnotationDbiaskpassbackportsBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootbroomcachemcarcarDataclassclicodetoolscolorspaceconfigcorpcorcorrplotcowplotcpp11crayoncurldata.tableDBIDelayedArrayDerivdirmultdoBydoParalleldplyre1071EpiDISHfarverfastmapforcatsforeachforecastformatRFormulafracdifffutile.loggerfutile.optionsgdatagenefiltergenericsGenomicRangesGGallyggplot2ggpubrggrepelggridgesggsciggsignifggstatsgluegmodelsgridExtragtablegtoolshmshttrIRangesisobanditeratorsjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelimmalme4lmtestlocfdrmagrittrMASSMatrixmatrixcalcMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrnlmenloptrnnetnnlsnumDerivopensslpatchworkpbapplypbkrtestpillarpkgconfigpngpolynompracmaprettyunitsprogressproxypurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRSQLiterstatixrsvdS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsysTCAtibbletidyrtidyselecttimeDateTOASTurcautf8vctrsviridisLitewithrXMLxtableXVectoryamlzoo

MICSQTL: Multi-omic deconvolution, Integration and Cell-type-specific Quantitative Trait Loci

Yue Pan, Qian Li

Rendered fromMICSQTL.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2024-03-08
Started: 2023-04-21