Skip to content

Latest commit

 

History

62 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Infernape

The goal of Infernape is to identify and quantify APA events from scRNA-seq data.

Please cite the paper "Kang, Bowei, Yalan Yang, Kaining Hu, Xiangbin Ruan, Yi-Lin Liu, Pinky Lee, Jasper Lee, Jingshu Wang, and Xiaochang Zhang. "Infernape uncovers cell type–specific and spatially resolved alternative polyadenylation in the brain." Genome Research 33, no. 10 (2023): 1774-1787."

Installation

You can install the development version of Infernape from GitHub with:

# install.packages("devtools")
devtools::install_github("kangbw702/Infernape")

Please install Infernape under R/4.0.0. Recommended versions of dependencies are as follows:

BiocGenerics_0.34.0
Biostrings_2.56.0
BSgenome_1.56.0
BSgenome.Mmusculus.UCSC.mm10_1.4.0
doParallel_1.0.15
foreach_1.5.0
dplyr_0.8.5
tidyr_1.1.0 
GenomicAlignments_1.24.0
GenomicRanges_1.40.0
GenomeInfoDb_1.24.0
ggplot2_3.3.1
IRanges_2.22.2
magrittr_1.5
MGLM_0.2.1
Matrix_1.4-1
plyr_1.8.6
Rsamtools_2.4.0
S4Vectors_0.26.1
tictoc_1.2

Example

This is a basic example which shows you how to solve a common problem. The data used for this example can be downloaded from here.

Function Infernape_cnt outputs raw peaks, peak annotation (before and after filtering), and peak by cell UMI count matrix.

library(Infernape)
genome = BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
Infernape_cnt(genome.ref = '../data/ref.csv',
              bam = '../data/TEGLU16.bam',
              batch.start = 2901,
              batch.end = 2920,
              ncores = 1,
              d = 31,
              h = 5,
              d.cut = 50,
              hr = 160,
              min.mode.prop = 0.05,
              min.mode.cutoff = 5,
              output.path = '../result',
              pas.reference.file = '../data/PAS_withinfo.csv',
              genome = genome,
              pas.search.cut.1 = 0,
              pas.search.cut.2 = 300,
              polystretch_length = 13,
              max_mismatch = 1,
              motif.search.cut = 300,
              invert_strand = FALSE,
              q = c(110, 200),
              whitelist.file = "../data/whitelist.TEGLU16.csv",
              start.cid = NULL,
              end.cid = NULL
)

Function Infernape_apa performs hierarchical differential APA testing.

Infernape_apa(counts.dir = '../result/cnt_mat',
              attr.file = '../data/attr.tbl.example.csv',
              anno.file = '../result/anno_filtered.csv',
              utr3.file = '../data/ref.utr3.anno.csv',
              ctype.colname = 'ctype',
              base_grp = 'c1',
              alt_grp = 'c2',
              cut.low.pct = 0.05,
              cut.pval = 0.05,
              cut.MPRO = 0.2,
              test.type = 'gene',
              out.dir = '../result'
)

References

3'UTR and PAS references for Human, Rat, and Caenorhabditis_elegans can be found here. Credit to Yalan Yang.

About

Identify and quantify 3'UTR peaks from scRNA-seq data

Resources

Stars

4 stars

Watchers

2 watching

Forks

Releases

Packages

Contributors

Languages