In genomicsclass/ph525x: support functions and data for edX course PH525

BiocStyle::markdown()

library(knitcitations)
library(bibtex)
allbib = read.bibtex("allbib.bib")

Introduction

This document describes some of the software and image interfaces provided in the ph525x package as a convenience for teaching and learning about Bioconductor in the edX PH525 series.

Design and object sketches

A simple schematic of the SEQC study

Sometimes it is easier to use a sketchpad to describe an experimental design. In the SEQC study (citation given in the figure below) two types of mRNA are analyzed separately and in specific mixtures. UHRR is Universal Human Reference RNA, and HBRR is Human Brain Reference RNA.

library(ph525x)
seqcDesign()

The abstract from the study can be seen via

seqcAbst()

The ExpressionSet schema

We use a composition of matrix and data.frame objects in an S4 class to represent information about microarray experiments in a coherent way.

esetDet1()

A Manhattan plot

The Manhattan plot is a classic approach to communicating simple statistical relationships between variation in DNA content (usually at the nucleotide level, focusing on single nucleotide polymorphisms, SNPs) and variation in disease risk or phenotypes measured in a cohort or population.

You can use this command to visualize such a plot, Figure 1 from Shungin et al. 2015; we don't do it here to avoid concerns with fairness of use.

obesManh()

Using Bioconductor you can create Manhattan plots fairly easily. For example, in connection with the EMBL GWAS catalog, we have

library(gwascat)
data(ebicat38)
seqlevelsStyle(ebicat38) = "UCSC"
traitsManh(ebicat38)

A view of RNA-seq alignments

It is good to have a quick way of assessing pileups of alignments over transcripts. In this case we have data from the HNRNPC knockdown study of Zarnack et al. in an Experimental Data package. This function uses the Gviz package on an extract from a BAM file provided by the experimenters in the ArrayExpress archive.

viewHreads14()

A view of the Epigenomics road map resources

Consortia have been formed to produce experimental results on the tendency of proteins that have been identified as transcription factors to bind to DNA extracted from diverse cell lines. Understanding the vocabularies and data formats for these experimental results takes effort; this display schematizes a small fraction of available results.

sydhTop()

More information on DNA-binding experiments in epigenomics can be obtained from the AnnotationHub and erma packages. The erma vignette illustrates how R can interface to the web browser to provide interactive tables of annotation.

Summary

This package contains utilities for simplifying certain aspects of teaching Bioconductor in edX. It will be updated and enhanced regularly as new concepts are addressed.

genomicsclass/ph525x documentation built on July 16, 2022, 1:37 p.m.