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https://github.com/alleninstitute/lowcat

Low coverage accessibility and transcriptomics

https://github.com/alleninstitute/lowcat

Science Score: 13.0%

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Keywords

atac-seq r transcriptomics
Last synced: 6 months ago · JSON representation

Repository

Low coverage accessibility and transcriptomics

Basic Info
  • Host: GitHub
  • Owner: AllenInstitute
  • License: other
  • Language: R
  • Default Branch: master
  • Size: 8.89 MB
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Topics
atac-seq r transcriptomics
Created about 8 years ago · Last pushed over 6 years ago
Metadata Files
Readme Contributing License

readme.md

lowcat: Low Coverage Accessibility and Transcriptomics

Rusty-spotted lowcat

Description

lowcat is a collection of functions for reading, comparing, clustering, and identifying single-cell ATAC-seq or other similar, low-coverage chromatin accessibility data.

Installation

lowcat depends on several Bioconductor packages. To start, install them with BiocManager: ``` if(!"BiocManager" %in% installed.packages()) { install.packages("BiocManager") }

bioc_packages <- c("GenomicAlignments", "GenomicRanges", "rsamtools", "rtracklayer")

missingbiocpackages <- setdiff(bioc_packages, installed.packages())

BiocManager::install(missingbiocpackages) ```

Then, install lowcat using: devtools::install_github("AllenInstitute/lowcat")

Reading files

The main unit of operation for lowcat is a list of GRanges objects, one per cell/nucleus/sample.

Note that this is not a GRangesList object.

lowcat has helper functions for reading in many BAM files (one per sample) or multiplexed BAM files.

For multiple BAM files, the fastest option is runpetofragparallel(): ``` mybamdir <- "/path/to/bamfiles/" bamfiles <- list.files(mybamdir, pattern = ".bam$", fullnames = TRUE)

bamnames <- list.files(mybamdir, pattern = ".bam$", fullnames = FALSE)

bamnames <- sub(".bam$", "", bamnames)

fragmentlist <- runpetofragparallel(bamfiles, samplenames = bamnames, n_cores = 4) ```

For multiplexed BAM data, like that from sci-ATAC-seq, use readmultiplexedpaired_bam().

Note 1: This requires that barcodes are present in the QNAME field of the BAM file.

Note 2: This function currently isn't very well optimized. It requires LOTS of available RAM - at least 4X the size of the target file itself, and can take a long time to run. fragment_list <- read_multiplexed_paired_bam(bam_file, barcode_start = 1, barcode_end = 32, read_length = 50, min_frags = 100, remove_duplicates = TRUE)

Level of Support

We are planning on occasional updating this tool with no fixed schedule. Community involvement is encouraged through both issues and pull requests.

License

This code is released under the Allen Institute Software License. See file LICENSE for details.

Contributions

Any contributions to this repository are subject to the Allen Institute Contribution Agreement. See file CONTRIBUTING.md for details.

Owner

  • Name: Allen Institute
  • Login: AllenInstitute
  • Kind: organization
  • Location: Seattle, WA

Please visit http://alleninstitute.github.io/ for more information.

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Dependencies

DESCRIPTION cran
  • GenomicAlignments * imports
  • GenomicRanges * imports
  • IRanges * imports
  • Rsamtools * imports
  • data.table >= 1.10.4 imports
  • dplyr >= 0.7.4 imports
  • parallel >= 3.4.3 imports
  • purrr >= 0.2.4 imports
  • rbamtools >= 2.16.0 imports
  • testthat * suggests