diff --git a/tests/data/.Rhistory b/tests/data/.Rhistory
deleted file mode 100644
index 5f45b69..0000000
--- a/tests/data/.Rhistory
+++ /dev/null
@@ -1,512 +0,0 @@
-??saveObject
-library(scRNAseq)
-sce <- ZilionisLungData()
-library(alabaster.base)
-dir_path <- paste(getwd(), "datasets", sep="/")
-saveObject(sce, path=paste(dir_path, "zilinoislung", sep="/"))
-# install alabaster
-BiocManager::install(c("ArtifactDB/alabaster.base"))
-BiocManager::install(version = "devel")
-# install alabaster
-BiocManager::install(c("ArtifactDB/alabaster.base"))
-BiocManager::install(version="devel")
-BiocManager::install(c("rhdf5"))
-q()
-BiocManager::install(c("rhdf5"))
-q()
-install.packages("BiocManager")
-BiocManager::install("rhdf5")
-BiocManager::install("rhdf5")
-BiocManager::install("rhdf5")
-BiocManager::install("rhdf5")
-BiocManager::install("artifactdb/alabaster")
-BiocManager::install("artifactdb/alabaster")
-BiocManager::install("artifactdb/alabaster")
-# install alabaster
-BiocManager::install(c("ArtifactDB/alabaster.base", "ArtifactDB/alabaster.sce", "ArtifactDB/alabaster.mae"))
-BiocManager::install(c("ArtifactDB/alabaster.base", "ArtifactDB/alabaster.sce", "ArtifactDB/alabaster.mae"))
-BiocManager::install("alabaster")
-BiocManager::install("alabaster")
-library(scRNAseq)
-library(alabaster)
-sce <- ZilionisLungData()
-sce
-saveRDS(sce[1:2000,], file = "/Users/kancherj/Projects/public/biocpy/tutorial/assets/data/zilinoislung.RDS")
-saveRDS(sce[,1:2000], file = "/Users/kancherj/Projects/public/biocpy/tutorial/assets/data/zilinoislung.RDS")
-saveRDS(sce[:,1:2000], file = "/Users/kancherj/Projects/public/biocpy/tutorial/assets/data/zilinoislung.RDS")
-saveRDS(sce[,1:2000], file = "/Users/kancherj/Projects/public/biocpy/tutorial/assets/data/zilinoislung.RDS")
-sce[,1:2000]
-sce[,1:2000]
-subset sce[,1:2000]
-subset <- sce[,1:2000]
-rowdata(subset)
-rowData(subset)
-rowRanges(subset)
-as.data.frame(rowRanges(sce))
-as.data.frame(as.genomicranges(rowRanges(sce))
-)
-as.data.frame(rowRanges(sce))
-unlist(rowRanges(sce))
-names(rowRanges(sce))
-DataFrame(genes=names(rowRanges(sce)))
-rowData(sce) <- DataFrame(genes=names(rowRanges(sce)))
-sce
-rowDAta(sce)
-rowData(sce)
-saveRDS(sce[,1:2000], file = "/Users/kancherj/Projects/public/biocpy/tutorial/assets/data/zilinois-lung-subset.rds")
-y <- rpois(112, lambda=8)
-names(y) <- 1:length(y)
-y
-saveRDS(y, file="atomic_ints_with_names.rds")
-sce <- ZilionisLungData()
-library(SingleCellExperiment)
-counts <- matrix(rpois(100, lambda = 10), ncol=10, nrow=10)
-sce <- SingleCellExperiment(counts)
-colData(sce) <- DataFrame(bool_null = c(NA, NA, TRUE, TRUE, NA, NA, NA, TRUE, TRUE, NA))
-library(GenomicRanges)
-gr <- GRanges(Rle(c("chr2", "chr1", "chr3", "chr1"), 4:1),
-IRanges(1:10, width=5),
-seqinfo=Seqinfo(c("chr1", "chr2", "chr3"), c(100, 50, 20)))
-gr <- GRanges(Rle(c("chr2", "chr1", "chr3", "chr1"), 4:1),
-IRanges(1:10, width=-1),
-seqinfo=Seqinfo(c("chr1", "chr2", "chr3"), c(100, 50, 20)))
-Iranges(1:10)
-IRanges(1:10)
-IRanges(start=1:10)
-IRanges(start=1:10, width=-1)
-IRanges(start=1:10, width=1)
-IRanges(start=1:10, width=1, end=10:30)
-IRanges(start=1:10, width=1, end=11:30)
-IRanges(start=1:10, end=11:30)
-library(gypsum)
-install.packages(gypsum)
-install.packages("gypsum")
-devtools::install_github("artifactdb/gypsum-R")
-library(devtools)
-BiocManager::install()
-BiocManager::install("gypsum")
-library(gypsum)
-fetchPermissions("test-R")
-path <- "foo/var.txt"
-base <- sub(".*/", "", path)
-library(gypsum)
-tmp <- tempfile()
-dir.create(tmp)
-write(file=file.path(tmp, "blah.txt"), LETTERS)
-dir.create(file.path(tmp, "foo"))
-write(file=file.path(tmp, "foo", "bar.txt"), 1:10)
-#'
-if (interactive()) {
-init <- startUpload(
-project="test-R",
-asset="upload-complete-check",
-version="v1",
-files=list.files(tmp, recursive=TRUE),
-probation=TRUE,
-directory=tmp
-)
-uploadFiles(init, directory=tmp)
-#'
-# Finishing the upload.
-completeUpload(init)
-}
-install.packages("digest")
-init <- startUpload(
-project="test-R",
-asset="upload-complete-check",
-version="v1",
-files=list.files(tmp, recursive=TRUE),
-probation=TRUE,
-directory=tmp
-)
-accessToken()
-setAccessToken()
-init <- startUpload(
-project="test-R",
-asset="upload-complete-check",
-version="v1",
-files=list.files(tmp, recursive=TRUE),
-probation=TRUE,
-directory=tmp
-)
-init <- startUpload(
-project="test-R-k",
-asset="upload-complete-check",
-version="v1",
-files=list.files(tmp, recursive=TRUE),
-probation=TRUE,
-directory=tmp
-)
-library(scRNAseq)
-sce <- fetchDataset("zeisel-brain-2015", "2023-12-14")
-sce
-library(scuttle_)
-library(scuttle)
-library(celldex)
-hpca_ref <- fetchReference("hpca", "2024-02-26")
-scuttle::logNormCounts(sce)
-library(SingleR)
-sce <- scuttle::logNormCounts(sce)
-cell_labels <- SingleR(
-test = assays(sce)[["logcounts"]],
-ref = assays(hpca_ref)[["logcounts"]]
-labels = hpca_ref$label.main)
-cell_labels <- SingleR(
-test = assays(sce)[["logcounts"]],
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-cell_labels
-library(scRNAseq)
-sce <- fetchDataset("zeisel-brain-2015", "2023-12-14")
-library(scuttle)
-library(celldex)
-hpca_ref <- fetchReference("hpca", "2024-02-26")
-# sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = assays(sce)[["logcounts"]],
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-table(cell_labels$labels)
-rownames(hpca_Ref)
-rownames(hpca_ref)
-hpca_ref$label.main
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-table(cell_labels$labels)
-hpca_ref$label.main
-View(cell_labels)
-View(as.data.frame(cell_labels))
-hpca_ref <- fetchReference("blueprint_encode", "2024-02-26")
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-table(cell_labels$labels)
-cell_labels$scores
-cell_labels$scores$HSC
-View(as.data.frame(cell_labels))
-cell_labels$scores.HSC
-cell_labels$scores[["HSC"]]
-hpca_ref <- fetchReference("immgen", "2024-02-26")
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-hpca_ref <- fetchReference("immgen", "2024-02-26")
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-library(scRNAseq)
-sce <- fetchDataset("zeisel-brain-2015", "2023-12-14")
-library(scuttle)
-library(celldex)
-hpca_ref <- fetchReference("immgen", "2024-02-26")
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = sce,
-ref = assays(hpca_ref)[["logcounts"]],
-labels = hpca_ref$label.main)
-library(scRNAseq)
-sce <- fetchDataset("zeisel-brain-2015", "2023-12-14")
-library(scuttle)
-library(celldex)
-hpca_ref <- fetchReference("immgen", "2024-02-26")
-library(SingleR)
-cell_labels <- SingleR(
-test = assay(sce, "counts")[,1:100],
-ref = hpca_ref,
-labels = hpca_ref$label.main)
-hpca_ref <- fetchReference("immgen", "2024-02-26")
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = assay(sce, "counts")[,1:100],
-ref = hpca_ref,
-labels = hpca_ref$label.main)
-bpnworkers(BPPARAM)
-cell_labels <- SingleR(
-test = assay(sce, "counts")[,1:100],
-ref = hpca_ref,
-labels = hpca_ref$label.main
-num.threads=4)
-cell_labels <- SingleR(
-test = assay(sce, "counts")[,1:100],
-ref = hpca_ref,
-labels = hpca_ref$label.main,
-num.threads=4)
-library(scRNAseq)
-sce <- fetchDataset("zeisel-brain-2015", "2023-12-14", realize.assays=TRUE)
-library(scuttle)
-library(celldex)
-hpca_ref <- fetchReference("immgen", "2024-02-26", realize.assays=TRUE)
-sce <- scuttle::logNormCounts(sce)
-library(SingleR)
-cell_labels <- SingleR(
-test = assay(sce, "counts")[,1:100],
-ref = hpca_ref,
-labels = hpca_ref$label.main,
-num.threads=4)
-library(GenomicRanges)
-gr <- GenomicRanges(
-seqnames = c("chr1", "chr1"),
-ranges = IRanges(c(2, 9), width=c(6, 11)),
-strand = c("+", "-"))
-gr <- GRanges(
-seqnames = c("chr1", "chr1"),
-ranges = IRanges(c(2, 9), width=c(6, 11)),
-strand = c("+", "-"))
-gr2 <- GRanges(
-seqnames = c("chr1"),
-ranges = IRanges(c(5), width=c(6)),
-strand = c("-"))
-intersect(gr, gr2)
-intersect(gr2, gr)
-library(AnnotationHub)
-ahub = AnnotationHub()
-ahub
-library(TxDb.Hsapiens.UCSC.hg38.knownGene)
-BiocManager::install(library(TxDb.Hsapiens.UCSC.hg38.knownGene))
-BiocManager::install(TxDb.Hsapiens.UCSC.hg38.refGene)
-BiocManager::install("TxDb.Hsapiens.UCSC.hg38.refGene")
-library(TxDb.Hsapiens.UCSC.hg38.refGene)
-TxDb.Hsapiens.UCSC.hg38.refGene
-library(genomicranges)
-library(GenomicRanges)
-as.granges(TxDb.Hsapiens.UCSC.hg38.refGene)
-genome <- TxDb.Hsapiens.UCSC.hg38.refGene
-genome
-transcripts(genome)
-seqlevels()
-seqlevels(genome)
-filtered <- keepSeqlevels(
-txpts,
-c("chr1", "chr2", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8",
-"chr9", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16",
-"chr17", "chr18", "chr19", "chr20", "chr21", "chr22", "chrX",
-"chrY"
-)
-)
-BiocManager::install("TxDb.Hsapiens.UCSC.hg38.refGene")
-library(TxDb.Hsapiens.UCSC.hg38.refGene)
-genome <- TxDb.Hsapiens.UCSC.hg38.refGene
-txpts <- transcripts(genome)
-filtered <- keepSeqlevels(
-txpts,
-c("chr1", "chr2", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8",
-"chr9", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16",
-"chr17", "chr18", "chr19", "chr20", "chr21", "chr22", "chrX",
-"chrY"
-)
-)
-seqname(genome)
-seqnames(genome)
-subset(txpts, seqnames(txpts) %in%   c("chr1", "chr2", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8",
-"chr9", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16",
-"chr17", "chr18", "chr19", "chr20", "chr21", "chr22", "chrX",
-"chrY"
-))
-x <- GRanges("chr1", IRanges(c(2, 9) , c(7, 19)), strand=c("+", "-"))
-library(GenomicRanges)
-x <- GRanges("chr1", IRanges(c(2, 9) , c(7, 19)), strand=c("+", "-"))
-y <- GRanges("chr1", IRanges(5, 10), strand="*")
-subtract(x,y)
-ignore.strand = FALSE
-minoverlap = 1
-y <- reduce(y, ignore.strand=ignore.strand)
-hits <- findOverlaps(x, y, minoverlap=minoverlap,
-ignore.strand=ignore.strand)
-hits
-extractList(y, as(hits, "IntegerList"))
-library(GenomicRanges)
-x <- GRanges("chr1", IRanges(c(2, 9) , c(7, 19)), strand=c("+", "-"))
-y <- GRanges("chr1", IRanges(5, 10), strand="+")
-subtract(x,y)
-ignore.strand = FALSE
-minoverlap = 1
-y <- reduce(y, ignore.strand=ignore.strand)
-hits <- findOverlaps(x, y, minoverlap=minoverlap,
-ignore.strand=ignore.strand)
-extractList(y, as(hits, "IntegerList"))
-ans <- psetdiff(x, extractList(y, as(hits, "IntegerList")))
-ans
-x = IRanges(c(1, 5, -2, 0, 14), width=c(10, 5, 6, 12, 4))
-y = IRanges(c(14, 0, -5, 6, 18), width=c(7, 3, 8, 3, 3))
-overlaps(x,y)
-find_overlaps(x,y)
-library(IRanges)
-x = IRanges(c(1, 5, -2, 0, 14), width=c(10, 5, 6, 12, 4))
-y = IRanges(c(14, 0, -5, 6, 18), width=c(7, 3, 8, 3, 3))
-find_overlaps(x,y)
-findOverlaps(x,y)
-findOverlaps(x,y, type="within")
-findOverlaps(x,y, type="start")
-library(tximportData)
-BiocManager::install("tximportData")
-dir <- system.file("extdata", package = "tximportData")
-list.files(dir)
-library(TxDb.Hsapiens.UCSC.hg19.knownGene)
-BiocManager::install("TxDb.Hsapiens.UCSC.hg19.knownGene")
-txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
-k <- keys(txdb, keytype = "TXNAME")
-tx2gene <- select(txdb, k, "GENEID", "TXNAME")
-library(TxDb.Hsapiens.UCSC.hg19.knownGene)
-txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
-k <- keys(txdb, keytype = "TXNAME")
-tx2gene <- select(txdb, k, "GENEID", "TXNAME")
-library(tximport)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene)
-BiocManager::install("tximport")
-library(tximport)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene)
-files <- file.path(dir, "salmon", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-all(file.exists(files))
-samples <- read.table(file.path(dir, "samples.txt"), header = TRUE)
-samples
-files <- file.path(dir, "salmon", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-all(file.exists(files))
-library(tximport)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene, ignoreTxVersion=TRUE)
-names(txi)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene,
-ignoreTxVersion=TRUE, ignoreAfterBar=TRUE)
-library(readr)
-BiocManager::install("readr")
-library(tximport)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene)
-tx2gene
-library(tximportData)
-dir <- system.file("extdata", package = "tximportData")
-list.files(dir)
-library(TxDb.Hsapiens.UCSC.hg19.knownGene)
-txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
-k <- keys(txdb, keytype = "TXNAME")
-tx2gene <- select(txdb, k, "GENEID", "TXNAME")
-samples <- read.table(file.path(dir, "samples.txt"), header = TRUE)
-samples
-library(readr)
-tx2gene <- read_csv(file.path(dir, "tx2gene.gencode.v27.csv"))
-BiocManager::install("readr")
-library(readr)
-tx2gene <- read_csv(file.path(dir, "tx2gene.gencode.v27.csv"))
-head(tx2gene)
-files <- file.path(dir, "salmon", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-all(file.exists(files))
-library(tximport)
-txi <- tximport(files, type = "salmon", tx2gene = tx2gene)
-names(txi)
-txi
-class(txi)
-txi.sum <- summarizeToGene(txi.tx, tx2gene)
-all.equal(txi$counts, txi.sum$counts)
-library(DESeq2)
-BiocManager::install("DESeq2")
-library(DESeq2)
-sampleTable <- data.frame(condition = factor(rep(c("A", "B"), each = 3)))
-rownames(sampleTable) <- colnames(txi$counts)
-dds <- DESeqDataSetFromTximport(txi, sampleTable, ~condition)
-library(DESeq2)
-library(DESeq2)
-sampleTable <- data.frame(condition = factor(rep(c("A", "B"), each = 3)))
-rownames(sampleTable) <- colnames(txi$counts)
-dds <- DESeqDataSetFromTximport(txi, sampleTable, ~condition)
-dds
-files <- file.path(dir, "salmon_gibbs", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-txi.inf.rep <- tximport(files, type = "salmon", txOut = TRUE)
-names(txi.inf.rep)
-library(tximport)
-txi.inf.rep <- tximport(files, type = "salmon", txOut = TRUE)
-names(txi.inf.rep)
-names(txi.inf.rep$infReps)
-library(DESeq2)
-sampleTable <- data.frame(condition = factor(rep(c("A", "B"), each = 3)))
-rownames(sampleTable) <- colnames(txi$counts)
-dds <- DESeqDataSetFromTximport(txi, sampleTable, ~condition)
-dds
-colData(dds)
-rowData(dds)
-txi
-names(txi)
-files <- file.path(dir, "salmon_gibbs", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-txi.inf.rep <- tximport(files, type = "salmon", txOut = TRUE)
-names(txi.inf.rep)
-names(txi.inf.rep$infReps)
-names(txi)
-names(txi.inf)
-View(txi.inf.rep)
-txi
-names(txi)
-txi$counts
-dims(txi$counts)
-dim(txi$counts)
-files <- file.path(dir, "salmon", samples$run, "quant.sf.gz")
-names(files) <- paste0("sample", 1:6)
-txi.salmon <- tximport(files, type = "salmon", tx2gene = tx2gene)
-head(txi.salmon$counts)
-dim(txi.salmon$counts)
-txi.inf.rep
-names(txi.inf.rep)
-names(txi.inf.rep$counts)
-dim(txi.inf.rep$counts)
-library(GenomicRanges)
-gr <- GRanges(
-seqnames = c("chr1", "chr1"),
-ranges = IRanges(c(2, 9), width=c(6, 11), mcols=DataFrame(a = 1:2)),
-strand = c("+", "-"))
-gr
-rnges(gr)
-ranges(gr)
-ir <- IRanges(c(2, 9), width=c(6, 11), mcols=DataFrame(a = 1:2))
-ir <- IRanges(c(2, 9), width=c(6, 11), mcols=DataFrame(a = 1:2))
-gr <- GRanges(
-seqnames = c("chr1", "chr1"),
-ranges = ir,
-strand = c("+", "-"))
-gr
-ir
-mcols(gr)
-setwd("~/Projects/public/BiocPy/rds2py/tests/data")
-y <- 10
-saveRDS(y, file="scalar_int.rds")
-type(y)
-x <- c(10, 20)
-type(x)
-class(x)
-class(y)
-z <- c(10)
-x == z
-x == y
-z == y
-y
-z
-x