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base repository: tolotos/opensnp_paper
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head repository: openSNP/opensnp_paper
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6 contributors

Commits on Dec 19, 2011

  1. added more citations

    @gedankenstuecke
    gedankenstuecke committed Dec 19, 2011
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  2. some more references

    @gedankenstuecke
    gedankenstuecke committed Dec 19, 2011
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  3. started working on discussion

    @gedankenstuecke
    gedankenstuecke committed Dec 19, 2011
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  4. finished first draft of discussion, added some dtc-privacy-pubs

    @gedankenstuecke
    gedankenstuecke committed Dec 19, 2011
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  5. first rework of draft :)

    @gedankenstuecke
    gedankenstuecke committed Dec 19, 2011
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Commits on Dec 20, 2011

  1. reworking of the draft, more references

    @gedankenstuecke
    gedankenstuecke committed Dec 20, 2011
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Commits on Jan 22, 2012

  1. Added a new introduction, structured the results and discussion, move… 

    …d a lot of paragraphs
    @tolotos
    tolotos committed Jan 22, 2012
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  2. some changes in the introduction

    @gedankenstuecke
    gedankenstuecke committed Jan 22, 2012
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Commits on Jan 23, 2012

  1. New structure for the sharing genotypes and the crowdsourcing phenoty… 

    …pes section. The verbatim package is used to create multi-line comments
    @tolotos
    tolotos committed Jan 23, 2012
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  2. Added new commenting system taken from here: http://stackoverflow.com… 

    …/questions/539791/tips-for-collaboratively-editing-a-latex-document/539848#539848; changed already present comments
    @tolotos
    tolotos committed Jan 23, 2012
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Commits on Jan 29, 2012

  1. worked on fabians comments

    @gedankenstuecke
    gedankenstuecke committed Jan 29, 2012
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Commits on Feb 3, 2012

  1. Fixed some typos, introduced JSON, changed some formulations

    @philippbayer
    philippbayer committed Feb 3, 2012
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Commits on Feb 8, 2012

  1. Wrote paragraph about the current DAS-methods

    @philippbayer
    philippbayer committed Feb 8, 2012
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Commits on Feb 27, 2012

  1. Added some details on DAS, changed some statistics (phenotypes missin… 

    …g, as user_snps is still counting), fixed some types, changed some sentences.
    @philippbayer
    philippbayer committed Feb 27, 2012
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  2. Reverted some stats to be congruent with pics

    @philippbayer
    philippbayer committed Feb 27, 2012
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Commits on Mar 3, 2012

  1. rewored draft with fabian

    @gedankenstuecke
    gedankenstuecke committed Mar 3, 2012
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Commits on Mar 4, 2012

  1. added citations

    @gedankenstuecke
    gedankenstuecke committed Mar 4, 2012
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Commits on Mar 20, 2012

  1. added images, wrote abstract

    @gedankenstuecke
    gedankenstuecke committed Mar 20, 2012
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Commits on Mar 25, 2012

  1. Replaced all don'ts etc by do not etc., fixed typos, started work on … 

    …more coherent abstract, changed DAS-citation to earlier in text, fixed all of Manuel's small tips
    @philippbayer
    philippbayer committed Mar 25, 2012
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  2. Added v2-chip numbers. Removed space in superscript page 2 paragraph … 

    …3 (we have to move footnotes to references anyway) Added dbSNP-citation to papers.bib and text
    @philippbayer
    philippbayer committed Mar 25, 2012
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  3. Fixed colons and lowercases. Put footnotes into references according to 

    http://blogs.plos.org/mfenner/2011/07/21/how-to-formally-cite-a-blog-post/
    @philippbayer
    philippbayer committed Mar 25, 2012
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Commits on Jul 17, 2012

  1. abstract redone

    @philippbayer
    philippbayer committed Jul 17, 2012
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  2. Ironed out sentences, shortened a lot, re-arranged some stuff

    @philippbayer
    philippbayer committed Jul 17, 2012
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  3. I'm trapped in GitHub, help, I have to live off too-long sentences

    @philippbayer
    philippbayer committed Jul 17, 2012
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  4. Minimal mistake fixed, stopping for today

    @philippbayer
    philippbayer committed Jul 17, 2012
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Commits on Jul 18, 2012

  1. Introduced tables for survey-results. Made transition survey/openSNP … 

    …easier.
    @philippbayer
    philippbayer committed Jul 18, 2012
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Commits on Aug 22, 2012

  1. made supplementary

    @gedankenstuecke
    gedankenstuecke committed Aug 22, 2012
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  2. restructure of paper itself

    @gedankenstuecke
    gedankenstuecke committed Aug 22, 2012
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  3. added new paper

    @gedankenstuecke
    gedankenstuecke committed Aug 22, 2012
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  4. added pdf-version

    @gedankenstuecke
    gedankenstuecke committed Aug 22, 2012
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Commits on Aug 28, 2012

  1. Reworked abstract a little

    @philippbayer
    philippbayer committed Aug 28, 2012
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  2. Merge branch 'master' of github.com:gedankenstuecke/opensnp_paper

    @philippbayer
    philippbayer committed Aug 28, 2012
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  3. Now the abstract flows better

    @philippbayer
    philippbayer committed Aug 28, 2012
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Commits on Sep 2, 2012

  1. Added R-code for plots

    @philippbayer
    philippbayer committed Sep 2, 2012
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  2. Added plots

    @philippbayer
    philippbayer committed Sep 2, 2012
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Commits on Sep 30, 2012

  1. Adding affiliations for Helge Rausch

    @tsujigiri
    tsujigiri committed Sep 30, 2012
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  2. Merge pull request #2 from tsujigiri/patch-1 

    Adding affiliations for Helge Rausch
    @gedankenstuecke
    gedankenstuecke committed Sep 30, 2012
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Commits on Oct 25, 2012

  1. Replaced old graphs by newest versions, added R-code, input-data to r… 

    …eproduce
    @philippbayer
    philippbayer committed Oct 25, 2012
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  2. erryday im merging

    @philippbayer
    philippbayer committed Oct 25, 2012
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  3. Added acknowledgment to openSNP's users

    @philippbayer
    philippbayer committed Oct 25, 2012
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  4. Wrong ylab for genotypes.svg

    @philippbayer
    philippbayer committed Oct 25, 2012
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Commits on Oct 26, 2012

  1. Re-introduced Survey into main-text

    @philippbayer
    philippbayer committed Oct 26, 2012
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  2. added citations, edited text to accommodate for PGP & genome.gov data

    @gedankenstuecke
    gedankenstuecke committed Oct 26, 2012
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Commits on Oct 27, 2012

  1. PNG-versions of the graphs, updated most stats (except # UserSNPs, st… 

    …ill counting), moved tables, inserted new graphs
    @philippbayer
    philippbayer committed Oct 27, 2012
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  2. Merge branch 'master' of github.com:gedankenstuecke/opensnp_paper 

    Conflicts:
	paper_draft.pdf
	paper_draft.tex
    @philippbayer
    philippbayer committed Oct 27, 2012
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  3. Added some more stats, changed title, only missing thing is the user-… 

    …snps-counter
    @philippbayer
    philippbayer committed Oct 27, 2012
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  4. Finished work on all stats-numbers about SNPs.

    @philippbayer
    philippbayer committed Oct 27, 2012
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Commits on Oct 28, 2012

  1. proofreading

    @gedankenstuecke
    gedankenstuecke committed Oct 28, 2012
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  2. Merge branch 'master' of github.com:gedankenstuecke/opensnp_paper

    @gedankenstuecke
    gedankenstuecke committed Oct 28, 2012
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Commits on Oct 29, 2012

  1. Added piechart and dotchart on distribution of annotational sources.

    @philippbayer
    philippbayer committed Oct 29, 2012
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numbers <- c(289, 1771, 3095, 8257, 11116)
names <- c("PGP", "PLOS", "NHGRI Catalog", "SNPedia", "Mendeley")
svg("papers_pie.svg")
pie(numbers, labels=names)
dev.off()

svg("papers_dotchart.svg")
dotchart(numbers, labels=names, xlab="Amount of annotational entries", xlim=c(0, 12000))
dev.off()
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1 28.09.2011 11:45
2 28.09.2011 12:52
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5 30.09.2011 07:40
6 01.10.2011 10:33
7 01.10.2011 10:34
8 01.10.2011 10:35
9 01.10.2011 10:38
10 01.10.2011 10:39
11 02.10.2011 03:05
12 02.10.2011 03:07
13 02.10.2011 03:11
14 02.10.2011 03:15
15 02.10.2011 04:04
16 05.10.2011 03:45
17 05.10.2011 03:50
18 05.10.2011 03:51
19 05.10.2011 04:10
20 10.10.2011 03:18
21 10.10.2011 16:01
22 17.10.2011 18:28
23 18.10.2011 02:03
24 18.10.2011 02:07
25 18.10.2011 06:57
26 24.10.2011 03:41
27 26.10.2011 15:11
28 26.10.2011 15:12
29 29.11.2011 17:52
30 29.11.2011 17:53
31 29.11.2011 18:00
32 01.12.2011 21:02
33 02.12.2011 00:31
34 02.12.2011 12:33
35 03.12.2011 00:55
36 03.12.2011 00:58
37 03.12.2011 01:02
38 03.12.2011 01:11
39 03.12.2011 01:11
40 03.12.2011 01:15
41 03.12.2011 01:22
42 03.12.2011 01:33
43 05.12.2011 22:05
44 06.12.2011 19:08
45 08.12.2011 17:41
46 27.12.2011 13:38
47 27.12.2011 13:40
48 27.12.2011 15:14
49 01.01.2012 17:35
50 01.01.2012 17:38
51 01.01.2012 17:41
52 04.01.2012 12:09
53 05.01.2012 22:12
54 13.01.2012 09:27
55 18.01.2012 12:57
56 22.02.2012 12:10
57 06.03.2012 15:43
58 12.03.2012 23:02
59 12.03.2012 23:03
60 16.03.2012 02:30
61 19.03.2012 02:29
62 20.03.2012 16:38
63 23.03.2012 17:45
64 24.03.2012 08:58
65 24.03.2012 09:03
66 24.03.2012 09:09
67 24.03.2012 17:04
68 24.03.2012 17:09
69 25.03.2012 18:32
70 27.03.2012 02:15
71 27.03.2012 02:23
72 27.03.2012 02:33
73 27.03.2012 02:37
74 29.03.2012 16:07
75 29.03.2012 16:18
76 07.04.2012 07:17
77 07.04.2012 07:31
78 07.04.2012 16:26
79 07.04.2012 16:29
80 07.04.2012 16:37
81 10.04.2012 11:55
82 10.04.2012 12:01
83 15.04.2012 15:51
84 28.04.2012 08:23
85 02.05.2012 19:03
86 03.05.2012 04:24
87 03.05.2012 04:32
88 03.05.2012 04:40
89 03.05.2012 10:41
90 07.05.2012 15:27
91 07.05.2012 15:33
92 07.05.2012 15:39
93 11.05.2012 16:42
94 14.05.2012 02:08
95 20.06.2012 13:57
96 06.07.2012 10:56
97 06.07.2012 11:01
98 12.07.2012 23:57
99 13.07.2012 00:32
100 18.07.2012 20:46
101 24.07.2012 21:56
102 24.07.2012 22:07
103 07.08.2012 16:54
104 14.08.2012 16:17
105 01.09.2012 12:26
106 04.09.2012 01:15
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108 04.09.2012 01:43
109 04.09.2012 01:54
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111 07.09.2012 03:37
112 08.09.2012 23:49
113 09.09.2012 01:51
114 09.09.2012 01:54
115 09.09.2012 21:06
116 10.09.2012 13:40
117 22.09.2012 14:52
118 01.10.2012 02:54
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123 16.10.2012 21:53
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130 21.10.2012 12:29
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svg("genotypes.svg")
genotypes <- read.table("genotypes.txt", sep="\t")
plot(strptime(genotypes[,2], format="%d.%m.%Y %H:%M"), genotypes[,1], type="l", ylab="Amount of genotypings",xlab="Time", xaxt="n")
dmin <- min(strptime(genotypes[,2], format="%d.%m.%Y %H:%M"))
dminjan <- as.POSIXct(format(dmin, "%Y-1-1"))
seqYear <- seq(dminjan, by = "1 month", to = max(strptime(genotypes[,2], format="%d.%m.%Y %H:%M")) + (86400 * 365))
axis(1, at = seqYear, labels = format(seqYear, "%b-%y"), las = 1)
dev.off()
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svg("phenotypes_vs_userphenotypes.svg")
par(mar=c(5, 4, 4, 6))
plot(sort(strptime(pheno[,2], "%d.%m.%Y %H:%M")), pheno[,1],type="l", xlab="Time", ylab="Amount of unique phenotypes",xaxt="n")
axis(1, at = seqYear, labels = format(seqYear, "%b-%y"), las = 1)
par(new=T)
plot(sort(strptime(usersp[,2], "%d.%m.%Y %H:%M")), usersp[,1],type="l",xlab="", yaxt="n",col="red",xaxt="n",ylab="")
axis(4,col.axis="red")
mtext("Amount of entered phenotypes", side=4,line=3,col="red")
dev.off()

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svg("users.svg")
users <- read.table("users.txt", sep="\t")
plot(strptime(users[,2], format="%d.%m.%Y %H:%M"), users[,1], type="l", ylab="Amount of user-accounts",xlab="Time", xaxt="n")
dmin <- min(strptime(users[,2], format="%d.%m.%Y %H:%M"))
dminjan <- as.POSIXct(format(dmin, "%Y-1-1"))
seqYear <- seq(dminjan, by = "1 month", to = max(strptime(users[,2], format="%d.%m.%Y %H:%M")) + (86400 * 365))
axis(1, at = seqYear, labels = format(seqYear, "%b-%y"), las = 1)
dev.off()
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14 changes: 7 additions & 7 deletions outline.txt
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@@ -65,10 +65,10 @@ to-do list together with outlook of personalised medicine

First focus on biological issues:

Polymorphisms to phenotypes, correlation only.
Bias in the samples collected by openSNP?
Sample size to small?
Quality check for phenotypes?
Polymorphisms to phenotypes, correlation only. done
Bias in the samples collected by openSNP? done
Sample size to small? done
Quality check for phenotypes? done
Mapping to haplotype blocks?
Combination with the hapmap
Manage increasing amount of data?
@@ -77,7 +77,7 @@ Manage increasing amount of data?
from great power follows great responsibility!

Imagine a world where all data is free...
What privacy issues do arise?
What privacy issues do arise? done
Is there an effective mechanism to avoid abuse or
genetic discrimination?
How should governments treat the additional data?
genetic discrimination? done
How should governments treat the additional data? done
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% Template for PLoS
% Version 1.0 January 2009
%
% To compile to pdf, run:
% latex plos.template
% bibtex plos.template
% latex plos.template
% latex plos.template
% dvipdf plos.template

\documentclass[10pt]{article}

% amsmath package, useful for mathematical formulas
\usepackage{amsmath}
% amssymb package, useful for mathematical symbols
\usepackage{amssymb}

% graphicx package, useful for including eps and pdf graphics
% include graphics with the command \includegraphics
\usepackage{graphicx}

% cite package, to clean up citations in the main text. Do not remove.
\usepackage{cite}

\usepackage{color}

% Use doublespacing - comment out for single spacing
%\usepackage{setspace}
%\doublespacing

%FZ: Enable the comment command
\usepackage{verbatim}
% Text layout
\topmargin 0.0cm
\oddsidemargin 0.5cm
\evensidemargin 0.5cm
\textwidth 16cm
\textheight 21cm

% Bold the 'Figure #' in the caption and separate it with a period
% Captions will be left justified
\usepackage[labelfont=bf,labelsep=period,justification=raggedright]{caption}

% Use the PLoS provided bibtex style
\bibliographystyle{plos2009}

% Remove brackets from numbering in List of References
\makeatletter
\renewcommand{\@biblabel}[1]{\quad#1.}
\makeatother


% Leave date blank
\date{}

\pagestyle{myheadings}
%% ** EDIT HERE **


%% ** EDIT HERE **
%% PLEASE INCLUDE ALL MACROS BELOW
\long\def\authornote#1{%
\leavevmode\unskip\raisebox{-3.5pt}{\rlap{$\scriptstyle\diamond$}}%
\marginpar{\raggedright\hbadness=10000
\def\baselinestretch{0.8}\tiny
\it #1\par}}
\newcommand{\bastian}[1]{\authornote{BG: #1}}
\newcommand{\fabian}[1]{\authornote{FZ: #1}}
\newcommand{\philipp}[1]{\authornote{PB: #1}}
%% END MACROS SECTION
\begin{document}

% Title must be 150 characters or less
\begin{flushleft}
{\Large
\textbf{openSNP - Crowdsourcing Genome-Wide Association Studies - Supplementary Methods}
}
% Alternative titles:
% openSNP - a new, open data-source for personalised medicine
% What kind of person would share genotyping-data? Presenting a survey and an open data-source for personalised medicine
%
% Insert Author names, affiliations and corresponding author email.
\\
Bastian Greshake$^{1,\ast}$,
Philipp Bayer$^{2}$,
Fabian Zimmer$^{3}$,
Julia Reda$^{4}$
\\
\bf{1} Goethe University, Frankfurt am Main, Germany
\\
\bf{2} University of Queensland, Brisbane, Australia
\\
\bf{3} Westf\"alische Wilhelms Universit\"at, M\"unster, Germany
\\
\bf{4} Johannes-Gutenberg University, Mainz, Germany
\\
$\ast$ E-mail: info@opensnp.org
\end{flushleft}

\section*{Introduction}
To evaluate whether customers of Direct-To-Consumer (DTC) genetic testing would be willing to share their raw data, along with phenotypic annotations, freely on the web a survey on the topic was set up and spread among customers and potential customers of DTC testing.

\section*{Materials and Methods}
\subsection*{Survey on Sharing Genetic Information}
The survey was performed using \textit{Google Docs} and was distributed to possible participants through the \textit{23andMe }community forums, the \textit{DIYBiology} mailing list,
blogs which focus on genetics and DTC genetic testing and social media like \textit{Twitter}, \textit{Google+} and \textit{Facebook}.

The survey included demographics such as age, chromosomal sex and ethnicity of the participants. Furthermore, it included questions on their
(planned) customer-ship with a DTC company. If the participants already were customers, they were also asked if they were already sharing their genetic and phenotypic data.
All participants were asked if they would share their genetical or phenotypic information with their DTC company, possible answers were "Yes", "Yes,
but only if they did not share my medical information with anybody else" and No".

The survey also asked some scaled questions which measured how strongly participants agreed/disagreed with different reasons for sharing or not sharing their
information. The scale went from 1 = strongly disagree to 5 = strongly agree. Motivations queried for sharing data
were "because I want to help scientists with their research", "because of possible personal benefits (e.g. getting treatments for a disease I have,
possibility of new medication, etc.)", "because it may deliver advertising that is relevant to me" and "out of curiosity". Motivations queried for not sharing
data were "because advertisers could use the information for targeted campaigns", "because of possible negative consequences for closely related persons",
"because of the breach of my privacy" and "because of the fear of discrimination (e.g. by the employer, the state, some insurance company)".
Additionally, participants had the possibility of giving their own reasons for sharing or not sharing their data.

The survey data was analyzed with SPSS 19.

% Results and Discussion can be combined.
\section*{Results}

\subsection*{Survey on Sharing Genetic Information}
In total 229 people, 180 with a self-reported chromosomal sex of XY and 56 with a self-reported chromosomal sex of XX participated in our survey on sharing genetic information with the public.
The mean age of the participants is 33 (SD = 11,29). 81.7 \% reported their ethnicity as caucasian. 39.7 \% of the participants are already
customers of at least one DTC genetic testing company and further 30.1 \% of them plan on becoming one in the future. 29.7 \% do not plan on
becoming a DTC customer. There is no significant difference in the usage of DTC companies between chromosomal sexes (Cramer's V = 0.077).

67.7 \% of all participants would share their data with their DTC-company without any constraints, 25.8 \% would do so given the company
didn't share the data with third parties. 6.6 \% of the participants would not share their data. Participants self-identified as XX-chromosomal are slightly more likely to answer that DTC companies are allowed to use their results (Cramer's V = 0.221). Those who are customers of a DTC company or are planning on becoming one in
the future are more likely to share their results, compared to those who do not plan on getting themselves genotyped (Somers-d = 0.331).


There are substantial differences in terms of motivation, tested by Tukey's HSD test, between those people who have already been genotyped
and those who are not planning on getting genotyped. The first group is likely to agree more strongly, on a five-point scale, with motivations for sharing genotypic information. On the other hand, those people who are not planning on getting genotyped are more likely to agree with the following motivations
for not sharing their data, see table \ref{tab:motivations1}.

\begin{table}
\begin{tabular}{|l|l|l|}
\hline
& Turkey's HSD & \\ \cline{2-3}
& Mean difference & SE \\ \hline
\textbf{Motivation for sharing genotypings in participants} & & \\
\textbf{who are already genotyped} & & \\ \hline
... curious & 1.159 & 0.193 \\
... want to help scientists & 0.465 & 0.128 \\
... for personal benefits & 0.448 & 0.183 \\ \hline
\textbf{Motivation for not sharing in participants} & & \\
\textbf{who are not planning to get genotyped} & & \\ \hline
... fear of discrimination & 1.06 & 0.195 \\
... breach of privacy & 0.821 & 0.225 \\
... fear of personalized advertising & 0.848 & 0.208 \\
... negative consequences for family members & 0.733 & 0.21 \\ \hline
\end{tabular}
\caption{Differences in terms of motivation to share genotypings with the public in survey-participants who already received a genotyping compared to participants who are not planning to getting genotyped. }
\label{tab:motivations1}
\end{table}

\begin{table}
\begin{tabular}{|l|l|l|}
\hline
& Turkey's HSD & \\ \cline{2-3}
& Mean difference & SE \\ \hline
\textbf{Motivation for sharing genotypings in participants} & & \\
\textbf{who would share with their DTC provider} & & \\ \hline
... curiosity & 1.99 & 0.321 \\
... want to help science & 1.57 & 0.199 \\
... for personal benefits & 0.951 & 0.308 \\ \hline
\textbf{Motivation for sharing genotypings in participants} & & \\
\textbf{who would not share with their DTC provider} & & \\ \hline
... fear of discrimination & 1.52 & 0.322 \\
... fear of consequences for family members & 1.146 & 0.32 \\
... fear of personalized advertising & 1.112 & 0.357 \\ \hline
\end{tabular}
\caption{Differences in terms of motivations to share genotyping-data, comparison between participants who would share their genotyping data with their DTC provider with participants who would not share their data with their DTC provider.}
\label{tab:motivations2}
\end{table}

Similarly, those people who would share data with their DTC provider under any circumstances are likely to agree more strongly with
the following motivations for sharing than those who would not share their data with their DTC company.
Those participants who are not willing to share data with their DTC company are likely to agree more strongly with the some motivations
for not sharing their data when compared to those who would share their data with their DTC company under any circumstances, for an overview of the motivations of both groups, see table \ref{tab:motivations2}.

In the case of curiosity as a motive, there is also a substantial difference between those who would share their data with their DTC company under the condition that it did not share the information and those who would not (mean difference = 1.116 SE = 0.344) as well as those who would share under any circumstances (mean difference = -0.874 SE = 0.182).

In the cases of fear of discrimination and fear of a breach of privacy, substantial differences between all three categories exist. Those who would share their data with their DTC company as long as it did not share the information agree less strongly than those who would not share the data with both fear of discrimination as a motive for not sharing (mean difference = -0.615, SE = 0.345) as well as fear of a breach of privacy (mean difference = -0.668, SE = 0.346). Those who would share their data under any circumstances are even less likely to agree with these motives than those who would share only if their DTC company did not share the information (fear of discrimination: mean value = -0.906, SE = 0.182; breach of privacy: mean difference = -1.203, SE = 0.183).

These survey-results indicate that there is a definite interest in customers of DTC-companies to share their results with other scientists.

\section*{Discussion}
As the survey was taken online by voluntary participants and was mainly spread in the personal genetics community,
and through social media the results do not necessarily reflect the general population.
Instead it's expected that it over-represents those people most likely to be interested in a project such as openSNP:
Customers of DTC genetic testing companies and people with a high interest in biology.

Due to those limitations it's not possible to get estimates of how many potential users could be acquired for a platform like openSNP.

\end{document}
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