Mapping chromatin structure and transactions

Interval analysis

bed_intersect() example

First, we’ll define some example intervals in x and y.

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Visual representation of the intersecting intervals.

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Tibble of the intersecting intervals.

Note

Note the addition of .x and .y suffixes to disamguate the input sources.

read_bed() example

Rse read_bed() to load genome annotations and signals.

Note

You’ll also use read_bedgraph() and read_bigwig() on your problem set.

What is in snps and genes?

Interval manipulation

Let’s find and characterize intergenic SNPs. We’ll use the tools bed_substract() and bed_closest(). Take a look and their examples in the valr documentation to see what they do.

Here, we’ll ask the question: “Which SNPs are intergenic, and how far are they from the nearest gene?”

Take a look at the intergenic and nearby objects in the console.

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Interval manipulation

Now that you have overlaps and distances between SNPs and genes, you can go back to dplyr tools to generate reports.

bed_map() example

bed_map() does two things in order:

1. It identifies intersecting intervals between x and y
2. Calculates summary statistics based on the intersection

A typical use is to count up signals (e.g., coverage from an MNase-seq experiment) over specific regions (e.g., promoter regions).

bed_map() example

Let’s setup some example data.

bed_map() example continued

First examine the intersecting intervals.

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Visual representation of bed_map()

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Computing multiple summaries with bed_map()