Data files for FastQDesign are hosted on Zenodo for reproducibility and easy access. Note: Some large data files (like BAM files and RDS objects) are not included in the R package due to size limits.
Download Links
BAM Files (scRNA-seq alignments)
Download from: https://zenodo.org/records/19073177
Contains Cellranger-aligned BAM files with cell barcodes (CB tag) and UMI (UB tag):
| File | Size |
|---|---|
P1_AI_possorted_genome_bam.bam |
13.1 GB |
P1_AI_possorted_genome_bam.bam.bai |
4.1 MB |
P1_BM_possorted_genome_bam.bam |
14.4 GB |
P1_BM_possorted_genome_bam.bam.bai |
4.4 MB |
Reference Data and Power Analysis
Download from: https://zenodo.org/records/19072084
Contains pre-processed Seurat objects and power analysis data:
| File | Description | Size |
|---|---|---|
reference_list.rds |
Reference SamplePrep output | 191.2 MB |
bam_downsample_list.rds |
Processed downsampled data | 77.9 MB |
AIBM_power.csv |
Power analysis data for experiment design | ~6 KB |
URL Streaming (No Download Required)
BAM files can be accessed directly from Zenodo URL without downloading.
Using Rsamtools
library(Rsamtools)
bam_url <- "https://zenodo.org/records/19073177/files/P1_AI_possorted_genome_bam.bam"
bai_url <- "https://zenodo.org/records/19073177/files/P1_AI_possorted_genome_bam.bam.bai"
bf <- BamFile(bam_url, index = bai_url)
header <- scanBamHeader(bf)Using fastF
fastF supports URL streaming for extract and
crb subcommands:
# Extract CR tags (UMI sequences)
# Processes 182M reads in ~8 minutes from URL
FastQDesign::fastF_extract(
bam = "https://zenodo.org/records/19073177/files/P1_AI_possorted_genome_bam.bam",
tag = "CR",
type = 0
)The extract subcommand streams BAM via htslib’s HTTP
support. For very large files, this is efficient as only necessary
regions are downloaded.
Local Download
# Download BAM
download.file(
"https://zenodo.org/records/19073177/files/P1_AI_possorted_genome_bam.bam",
destfile = "P1_AI_possorted_genome_bam.bam"
)
# Download Seurat object
download.file(
"https://zenodo.org/records/19072084/files/reference_list.rds",
destfile = "reference_list.rds"
)
library(Seurat)
seurat_obj <- readRDS("reference_list.rds")