Package: MICSQTL 1.3.2

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_1.3.2.tar.gz
MICSQTL_1.3.2.zip(r-4.5)MICSQTL_1.3.2.zip(r-4.4)MICSQTL_1.3.2.zip(r-4.3)
MICSQTL_1.3.2.tgz(r-4.4-any)MICSQTL_1.3.2.tgz(r-4.3-any)
MICSQTL_1.3.2.tar.gz(r-4.5-noble)MICSQTL_1.3.2.tar.gz(r-4.4-noble)
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MICSQTL.pdf |MICSQTL.html✨
MICSQTL/json (API)
NEWS

# Install 'MICSQTL' in R:

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

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

Datasets:

se - Example data

On BioConductor:MICSQTL-1.3.2(bioc 3.20)MICSQTL-1.2.2(bioc 3.19)

bioconductor-package

4 exports 1.16 score 143 dependencies

Last updated 2 months agofrom:c954df3dbe

Exports:ajive_decomp csQTL deconv feature_filter

Dependencies:abind askpass backports BH Biobase BiocGenerics BiocParallel bit bit64 boot broom broom.helpers car carData class cli clipr codetools colorspace config corpcor corrplot cowplot cpp11 crayon curl data.table DelayedArray Deriv dirmult doBy doParallel dplyr e1071 EpiDISH fansi farver forcats foreach formatR futile.logger futile.options gdata generics GenomeInfoDb GenomeInfoDbData GenomicRanges GGally ggplot2 ggpubr ggrepel ggridges ggsci ggsignif ggstats glue gmodels gridExtra gtable gtools haven hms httr IRanges isoband iterators jsonlite labeling labelled lambda.r lattice lifecycle limma lme4 locfdr magrittr MASS Matrix matrixcalc MatrixGenerics MatrixModels matrixStats mgcv microbenchmark mime minqa modelr munsell nlme nloptr nnet nnls numDeriv openssl patchwork pbapply pbkrtest pillar pkgconfig plyr polynom pracma prettyunits progress proxy purrr quadprog quantreg R6 RColorBrewer Rcpp RcppEigen readr rlang rstatix rsvd S4Arrays S4Vectors scales snow SparseArray SparseM statmod stringi stringr SummarizedExperiment survival sys TCA tibble tidyr tidyselect TOAST tzdb UCSC.utils utf8 vctrs viridisLite vroom withr XVector yaml zlibbioc

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

Yue Pan, Qian Li

Rendered fromMICSQTL.Rmdusingknitr::rmarkdownon Jul 08 2024.

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

Help page	Topics
Integrative analysis for modes of joint variation	ajive_decomp
Cell-type-specific differential expression (csQTL)	csQTL
Estimation of cellular composition in high-throughput data from heterogeneous tissues	deconv
Feature filtering	feature_filter
Example data	se

Package: MICSQTL 1.3.2

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

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

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Readme and manuals

Help Manual

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