hammerlab/rinfino

Name: rinfino

Owner: Hammer Lab

Description: R client to run infino (http://github.com/hammerlab/infino)

Created: 2017-11-22 18:33:42.0

Updated: 2017-12-07 21:23:40.0

Pushed: 2018-01-11 07:10:27.0

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Size: 175603

Language: R

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README

rinfino

The goal of rinfino is to provide helper-functions and (eventually) an interface to infino. Infino is a computational biology tool that estimates the composition of immune infiltrate in a bulk-biopsy sample given RNAseq data using a Bayesian hierarchical mixture model.

Installation

You can install rinfino from github with:

stall.packages("devtools")
ools::install_github("hammerlab/rinfino")

Since this package makes use of Bioconductor packages, you may prefer to use biocLite to install from github:

urce("https://bioconductor.org/biocLite.R")
Lite('hammerlab/rinfino')

Example

Load an example dataset, filter to genes that are expressed in at least one sample & run PCA:

ary(dplyr)
ary(rinfino)
("rcctils_expression")

results <- 
ctils_expression %>% 
lter_expdata(fun = function(x) {max(x)>0}) %>% 
n_pca(use_ggplot=T)

Alternatively, you might want to load data from multiple sources (say, TCGA & a sample of isolated tils), filter to marker genes & run combat:

ary(dplyr)
ary(rinfino)

_to_rcctils <- system.file("testdata", "rcctils_expression_matrix.tsv.gz", package = "rinfino")
_to_tcgaexp <- system.file("testdata", "tcga_expression_matrix.tsv.gz", package = "rinfino")

at_results <-
ad_all_expdata(c(path_to_rcctils, path_to_tcgaexp), batch = c('rcctils', 'tcgaexp')) %>%
lter_expdata() %>%  ## filter to expressed genes
n_pca(use_ggplot=F) %>% ## run_pca
lter_genes() %>%  ## filter to marker genes
n_combat()