Plot coverage in nuclear and cytoplasmic RNA for candidate probe sequences.

Source: R/plot_coverage.R

plot_coverage plots the coverage of nuclear and cytoplasmic RNA from adult and prenatal human prefrontal cortex across a candidate or series of candidate probe sequences for BrainFlow. If the sequence spans splice junctions, the plot will include the introns. A good candidate sequence will be highly and evenly expressed in nuclear RNA.

plot_coverage(
  REGION,
  PDF = "regionCoverage_fractionedData.pdf",
  OUTDIR = tempdir(),
  COVERAGE = NULL,
  CODING_ONLY = FALSE,
  VERBOSE = TRUE
)

Arguments

REGION

Either a single hg19 genomic sequence including the chromosome, start, end, and optionally strand separated by colons (e.g., 'chr20:10199446-10288068:+'), or a string of sequences. Must be character. Chromosome must be proceeded by 'chr'.

PDF

The name of the PDF file. Defaults to regionCoverage_fractionedData.pdf.

OUTDIR

The default directory where PDF will be saved to.

COVERAGE

The output of brainflowprobes_cov for the input REGION. Defaults to NULL but it can be pre-computed and saved separately since this is the step that takes the longest to run. Also, this is the only step that depends on rtracklayer's functionality for reading BigWig files which does not run on Windows OS. So it could be run on a non-Windows machine, saved, and then shared with Windows users.

CODING_ONLY

A logical vector of length 1 specifying whether to subset the Annotated Genes to only the coding genes. That is, whether to subset the genes by whether they have a non-NA CSS value. The Annotated Genes are downloaded with GenomicState::GenomicStateHub().

VERBOSE

A logical value indicating whether to print updates from the process of loading the data from the BigWig files.

Value

plot_coverage plots all input sequences using derfinderPlot::plotRegionCoverage(). It returns a plot for each input candidate sequence listed in REGION. Each plot includes coverage of the sequence(s) in nuclear (N) and cytoplasmic (C) RNA isolated from adult (A) and fetal (F) prefrontal cortex, sequenced using two different library preparation methods. PolyA+ libraries (P) were generated using selection for polyadenylated transcripts, and RiboZero (R) libraries were generated using a ribosomal RNA depletion protocol.

Each plot also shows the overlapping genes beneath the coverage, and the genomic location. The title lists the nearest gene, the position of the sequence relative to the gene's canonical transcriptional start site (TSS), and further annotation information as described in the 'region' column from bumphunter::matchGenes().

plot_coverage saves the results as regionCoverage_fractionedData.pdf in a temporary directory unless otherwise specified with OUTDIR.

Author

Amanda J Price

Examples


## Here we use the pre-saved example coverage data such that this example
## will run fast!
plot_coverage("chr20:10286777-10288069:+",
    COVERAGE = four_panels_example_cov
)
#> loading from cache
#> loading from cache
#> 2023-05-07 06:27:01.480368 annotateRegions: counting
#> 2023-05-07 06:27:02.895399 annotateRegions: annotating
#> 2023-05-07 06:27:03.121126 Completed! Check for /tmp/Rtmp3fU3Pu/regionCoverage_fractionedData.pdf.

## Without using COVERAGE, this function reads BigWig files from the web
## using rtracklayer and this functionality is not supported on Windows
## machines.
if (.Platform$OS.type != "windows") {
    plot_coverage("chr20:10286777-10288069:+",
        PDF = "regionCoverage_fractionedData_fromScratch.pdf"
    )
}
#> loading from cache
#> loading from cache
#> 2023-05-07 06:27:18.387853 annotateRegions: counting
#> 2023-05-07 06:27:18.976636 annotateRegions: annotating
#> 2023-05-07 06:27:19.08606 getRegionCoverage : attempting to load coverage data from 'files'.
#> 2023-05-07 06:27:19.09772 fullCoverage: processing chromosome chr20
#> 2023-05-07 06:27:19.11821 loadCoverage: finding chromosome lengths
#> 2023-05-07 06:27:19.34331 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br1113C1_polyA.bw
#> 2023-05-07 06:27:19.738588 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br1113N1_polyA.bw
#> 2023-05-07 06:27:20.146545 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2046C_polyA.bw
#> 2023-05-07 06:27:20.534804 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2046N_polyA.bw
#> 2023-05-07 06:27:20.880288 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2074C_polyA.bw
#> 2023-05-07 06:27:22.345428 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2074N_polyA.bw
#> 2023-05-07 06:27:22.711935 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5339C1_polyA.bw
#> 2023-05-07 06:27:23.071987 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5339N1_polyA.bw
#> 2023-05-07 06:27:23.419618 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5340C1_polyA.bw
#> 2023-05-07 06:27:23.768357 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5340N1_polyA.bw
#> 2023-05-07 06:27:24.11167 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5341C1_polyA.bw
#> 2023-05-07 06:27:24.492876 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5341N1_polyA.bw
#> 2023-05-07 06:27:24.867908 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br1113C1_RiboZero.bw
#> 2023-05-07 06:27:25.221257 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2046C_RiboZero.bw
#> 2023-05-07 06:27:25.587989 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2046N_RiboZero.bw
#> 2023-05-07 06:27:25.933481 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2074C_RiboZero.bw
#> 2023-05-07 06:27:26.279156 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br2074N_RiboZero.bw
#> 2023-05-07 06:27:26.617171 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5339C1_RiboZero.bw
#> 2023-05-07 06:27:26.961305 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5339N1_RiboZero.bw
#> 2023-05-07 06:27:27.301182 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5340C1_RiboZero.bw
#> 2023-05-07 06:27:27.639771 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5340N1_RiboZero.bw
#> 2023-05-07 06:27:27.981568 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5341C1_RiboZero.bw
#> 2023-05-07 06:27:28.376316 loadCoverage: loading BigWig file http://brain-flow-rna.s3.us-east-2.amazonaws.com/Sep/Br5341N1_RiboZero.bw
#> 2023-05-07 06:27:28.714921 loadCoverage: applying the cutoff to the merged data
#> 2023-05-07 06:27:28.926351 filterData: originally there were 63025520 rows, now there are 63025520 rows. Meaning that 0 percent was filtered.
#> 2023-05-07 06:27:28.99449 getRegionCoverage: processing chr20
#> 2023-05-07 06:27:29.080237 getRegionCoverage: done processing chr20
#> 2023-05-07 06:27:29.195568 Completed! Check for /tmp/Rtmp3fU3Pu/regionCoverage_fractionedData_fromScratch.pdf.
if (FALSE) {

## These examples will take a few minutes to run!
plot_coverage(c(
    "chr20:10286777-10288069:+",
    "chr18:74690788-74692427:-",
    "chr19:49932861-49933829:-"
))

candidates <- c(
    "chr20:10286777-10288069:+",
    "chr18:74690788-74692427:-",
    "chr19:49932861-49933829:-"
)

## General syntax:
plot_coverage(candidates,
    PDF = "PDF_file.pdf",
    OUTDIR = "/path/to/directory/"
)

plot_coverage("chr20:10286777-10288069:+",
    PDF = "PDF_file.pdf", OUTDIR = "/path/to/directory/"
)

## Explore the effect of changing CODING_ONLY
## Check how gene name and distance to TSS changes in the title of the plot
## (everything else stays the same)
cov <- brainflowprobes_cov("chr10:135379301-135379311:+")
plot_coverage("chr10:135379301-135379311:+", COVERAGE = cov)
plot_coverage("chr10:135379301-135379311:+",
    COVERAGE = cov,
    PDF = "coding_only_plot_coverage", CODING_ONLY = TRUE
)
}