mikelove

library(airway)
library(tidySummarizedExperiment)
library(plyxp)
data(airway)
se <- airway
rowRanges(se) <- NULL

forced_conversion <- function(se) {
  tib <- tidySummarizedExperiment:::as_tibble.SummarizedExperiment(se)
  res <- tib |> 

mikelove

# adapted from DFplyr
# ignoring rownames and GroupedDataFrame functionality...
left_join.DataFrame <- function(x, y, by = NULL, ...) {
  if (is.null(by)) {
    by <- intersect(names(x), names(y))
    if (length(by) == 0) {
      rlang::abort("`by` must be supplied when `x` and `y` have no common variables.")
    }
    message("Joining with `by = ", deparse(by), "`")
  }

mikelove

❯ checking examples ... [14s/14s] ERROR
  Running examples in ‘plyranges-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: read_bed
  > ### Title: Read a BED or BEDGraph file
  > ### Aliases: read_bed read_bed_graph read_narrowpeaks
  > 
  > ### ** Examples

mikelove

library(here)
library(plyranges)
source(here("analysis/common/import.R"))

# This script imports variant-level summary statistics and adds QC variables
# e.g. 
# - sufficient activity of at least one of the alleles
# - balanced representation of reference and 
#   alternate alleles in the input DNA

mikelove

library(GenomicRanges)
library(GenomicFeatures)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)

txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene
ebt <- exonsBy(txdb, by="tx")
cbt <- cdsBy(txdb, by="tx")
fubt <- fiveUTRsByTranscript(txdb)
tubt <- threeUTRsByTranscript(txdb)

mikelove

library(DESeq2)
dds <- makeExampleDESeqDataSet()
dds_leaf <- dds[1:500,]
dds_inner <- dds[501:1000,]
dds_leaf <- DESeq(dds_leaf)
res_leaf <- lfcShrink(dds_leaf, coef="condition_B_vs_A", type="apeglm")

# this runs DESeq2 on inner nodes but using priors from leaves
sizeFactors(dds_inner) <- sizeFactors(dds_leaf)
dds_inner <- estimateDispersionsGeneEst(dds_inner)

mikelove

library(tidySummarizedExperiment)
library(plyxp)

nfeat <- 1e4
nsamp <- 1e3
coldata <- data.frame(x=rep(1:2,length=nsamp))
assay <- matrix(rnorm(nfeat*nsamp), ncol=nsamp)
rownames(assay) <- paste0("f",1:nfeat)
colnames(assay) <- paste0("s",1:nsamp)

mikelove

library(dplyr)
library(tidyr)
library(purrr)

simulate_genotype <- function(maf, n) rbinom(n, 2, maf)

simulate_data <- function(beta, maf, n) {
  data.frame(
    genotype = simulate_genotype(maf, n)
  ) |>

mikelove

> x <- data.frame(seqnames="chr1", start=c(1,101), width=100, foo=c("bar","boo")) |> as_granges()
> x
GRanges object with 2 ranges and 1 metadata column:
      seqnames    ranges strand |         foo
         <Rle> <IRanges>  <Rle> | <character>
  [1]     chr1     1-100      * |         bar
  [2]     chr1   101-200      * |         boo
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths
> x |> tile_ranges(25)

mikelove

# Created by chat GPT

# Load necessary libraries
library(splines)
library(GPfit)

# Set seed for reproducibility
set.seed(123)

# Generate non-uniform data