A Guide to QTL Mapping with R/qtl: Online complements

This page contains online complements to A Guide to QTL Mapping with R/qtl, by Karl W. Broman and Śaunak Sen.

Buy the book
Sample data files
Contact the authors
Sample chapter (pdf)

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Our aim in this book is to give an overview of the practical aspects of the analysis of QTL mapping experiments based on inbred line crosses, with explicit instructions on the use of the R/qtl software (an add-on package for R). We give some of the details of the statistical methods, but mostly focus on how to get and make sense of results. Real data examples are included throughout.

The intended audience includes scientists who are performing QTL mapping experiments and want to participate directly in the analysis. Some readers will be statisticians analyzing data from QTL experiments with a basic understanding of genetics.

All of the R code used in the book, including the detailed code used to create the figures, is available in files below, under Software. In addition, we have created an R package, R/qtlbook, that contains all of our example data sets (except those already included in R/qtl); it is also available under Software, below.


Q Zhou (2010) Journal of Statistical Software Vol. 32, Book Review 5 [pdf (133k)]

"In sum, this is a well-written book with carefully chosen and nicely organized topics. It can serve as a good introduction to QTL mapping methodology and a useful practical guide to the R package."

RW Doerge (2010) Biometrics 66(2):658-659 [html | pdf (152k)]

"The authors should be commended on presenting a well-written book that is understandable, and in-depth enough, to be considered a responsible treatment of QTL mapping for anyone who is interested."

Jinx (Leslie Turner, personal communication) [jpeg]              



Detailed contents as PDF: contents.pdf

1   Introduction
2   Importing and simulating data
3   Data checking
4   Single-QTL analysis [Sample chapter (pdf)]
5   Non-normal phenotypes
6   Experimental design and power
7   Working with covariates
8   Two-dimensional, two-QTL scans
9   Fit and exploration of multiple-QTL models
10  Case study I
11  Case study II
A  Installing R and R/qtl
B  List of functions in R/qtl [pdf]
C  QTL mapping data sets
D  Hidden Markov models for QTL mapping


Major errata:

  1. Chapter 3, page 53, second paragraph: the sentence
    Individuals 5 and 138 have identical genotypes at all 86 markers at which they were both typed; individuals 12 and 55 have the same genotype at 75/76 markers.

    should be replaced with

    Individuals 12 and 55 have identical genotypes at all 86 markers at which they were both typed; individuals 5 and 138 have the same genotype at 75/76 markers.

    That is, we had the two pairs reversed.

  2. Chapter 8, page 234, Table 8.2 has a couple of errors.

    The number of degrees of freedom for LODa for A:X should be 8 – 3 = 5 (not 8).

    The number of degrees of freedom for LODfv1 for X:X should be 12 – 6 = 6 (not 3).

    The table should appear as follows.

  3. Chapter 11, page 349, Fig. 11.14 is seriously messed up.

    The figure should appear as follows. (Click the image to see a larger version.)

  4. Appendix D, page 381, Table D.2 has a couple of errors.

    Pr(O=C | G=AA) = ε (not ε/2)

    Pr(O=D | G=BB) = ε (not ε/2)

    The table should appear as follows.

Minor errata:

  1. Chapter 1, pages 4 and 5, legends to Fig. 1.1 and 1.2: Where we say "blue and pink", we should have said "blue and red".
  2. Chapter 1, page 8, lines 3-4 of first paragraph: Change "if there is there is an average..." to "if there is an average...".
  3. Chapter 7, page 186, line 5 of the first paragraph: Change "let us us separate the..." to "let us separate the...".
  4. Appendix D, page 381, line 4: Change "possibly genotyping errors" to "possible genotyping errors".


R web page

R/qtl web page [Download page]

R/qtlbook package (with the example data used in the book):
 Unix source: qtlbook_0.18-1.tar.gz (2 Nov 2011)
Mac OS X binary:qtlbook_0.18-1.tgz
Windows binary:qtlbook_0.18-1.zip

R/qtlDesign web page [Unix source (ver 0.941, 8 Sep 2010)]

R code from the book:

Chapter File(s)

 2 Importing and simulating data chap02.R
3 Data checking chap03.R
4 Single-QTL analysis chap04.R
5 Non-normal phenotypes chap05.R, scanone_cph.R
6 Experimental design and power chap06.R
7 Working with covariates chap07.R
8 Two-dimensional, two-QTL scans chap08.R
9 Fit and exploration of multiple-QTL models chap09.R
10 Case study I chap10.R
11 Case study II chap11.R

Detailed R code for all figures in the book:

Chapter File(s)

 1 Introduction fig01.R, meiosis_func.R
 2 Importing and simulating data fig02.R
3 Data checking fig03.R
4 Single-QTL analysis fig04.R
5 Non-normal phenotypes fig05.R
6 Experimental design and power fig06.R
7 Working with covariates fig07.R
8 Two-dimensional, two-QTL scans fig08.R
9 Fit and exploration of multiple-QTL models fig09.R
10 Case study I fig10.R
11 Case study II fig11.R

All of the code from the book compressed into one file: RqtlBook_Code.tgz

Sample data files

Samples of data files for import into R/qtl, in a variety of formats and with the necessary R code, are available here.

Contact the authors

Karl W. Broman   Śaunak Sen
Department of Biostatistics and Medical Informatics Department of Epidemiology and Biostatistics
University of Wisconsin-Madison University of California, San Francisco
kbroman at biostat.wisc.edu sen at biostat.ucsf.edu