SNPEVG is a set of graphical tools for instant global and local viewing and graphing of GWAS results for all chromosomes and for each trait. (Genome-wide association study investigates the association between a huge amount of genetic loci and different traits/diseases

1. SNPEVG---SNP Effect Viewing
and Graphing

2. GROUP MEMBERS:
• MAIRA KHAN
• HIRA BATOOL
• MARYAM ZAHRAH
• NADIA ASHRAF

3. INTRODUCTION
• SNPEVG is a set of graphical tools for instant
global and local viewing and graphing of
GWAS results for all chromosomes and for
each trait. (Genome-wide association study
investigates the association between a huge
amount of genetic loci and different
traits/diseases)
• Implemented in the C++ programming
language

4. IMPORTANCE
• Exploring traits/diseases-associated SNPs (TASs)
which have relatively high signals from GWAS or
whole genome sequencing association study needs
further downstream statistical inference and
bioinformatics prediction.
• As indispensable steps, variants visualization,
functional annotation and selection of risk associated
locus greatly facilitate the discovery of true
association between genetic marker and
disease/trait.
• Detailed graphical examination of each chromosome
is helpful for further understanding the GWAS results

5. SNPEVG Package-Version 3.2
• Includes three graphical programs:
SNPEVG1
SNPEVG2
SNPEVG3

6. The SNPEVG1 program
• Creates Manhattan plots and Q-Q plots providing
global view of test results for each trait.
• SNPEVG1 supports a maximum 100 traits.
• Assuming 30 traits and 30 chromosomes per trait, one
command of ‘Run’ produces 960 graphs including 30
Manhattan plots, 30 Q-Q plots and 900 chromosome
graphs. This will greatly facilitate the digestion of
GWAS results.
• The total number of graphs that can be generated by
one ‘Run’ is n(c + 2), where n is number of ‘traits’ with
0<n≤100, and c is the number of chromosomes.

7. INPUT File
• SNPEVG1 requires a simple text input file with
the following columns: CHR, POSITION, SNP, and
P-VALUE columns
• CHR = chromosome number,
• POSITION = chromosomal position of the SNP
marker,
• SNP = name of the SNP marker,
• P-VALUE is the P-value for a trait.
• extension ‘snpe’.

8. EXAMPLE
SNPID Chr Position T1-geno T1-add T1-dom T2-geno T2-add T2-dom
SNP01 1 571340 2.48E-03 1.11E-03 1.58E-03 2.74E-02 2.65E-01 1.11E-03
SNP02 1 845494 7.02E-04 9.07E-04 8.91E-05 2.56E-02 8.02E-02 9.07E-04
SNP03 1 883895 1.87E-02 1.71E-01 3.07E-03 1.07E-02 2.81E-03 1.71E-01
SNP04 1 929617 1.79E-03 1.57E-02 1.39E-05 9.03E-02 2.99E-04 1.57E-02

9. GUI

10. Trait Selection

11. Manhattan plot
• The Manhattan plot allows all SNP effects of all
chromosomes per trait on one graph to quickly
identify genome locations with the most
significant SNP effects.
• Each Manhattan plot uses true chromosome size
defined by the starting and ending SNP marker
positions of the chromosome.
• P-values for the unknown chromosome are
displayed in sequential order of SNP markers
rather than chromosome positions

14. Manhattan plot setting for pixel sizes and chromosome colors (upper) and
Manhattan plot with threshold P-value line (lower).

15. Manhattan plot with threshold P-value line and without showing data points
below cut-off P-value.

16. Q-Q Plot for all SNP Effects

17. • For each chromosome, P-values can be presented as
connected lines (Fig. A) or separate symbols(Fig.B).

18. OUTPUT FILE FORMAT
• Any selected graph, or graphs for selected
traits, or all graphs can be saved as graphical
images(.png files) with publication quality by
clicking a button on the GUI.

19. The SNPEVG2 program
• Multiple traits/values per graph
• Any method of significance testing
• Any values of variables
• 2 Y-Axes.

20. FEATURES
• Instant graphics of large quantities of genome-wide
significance testing results or original values from any
selected significance effects and original values.
• Support of ‘Y1’ and ‘Y2’ axes and selection of values for
either axis.
• Immediate viewing of all graphics within the SNPEVG2
GUI.
• Scalable SNPEVG2 GUI allowing efficient and flexible use
of computer screen.
• Graphics of Manhattan plot, Q-Q plot, and figures for all
chromosomes and all effects/values (up to 100
effects/values) by one click of ‘run’.
• Save of one graph or all graphs for all Manhattan plots, Q-
Q plots, and chromosomes by one of ‘Current Graph’ or
‘All Graphs’.

21. GUI

23. Example of genetic effects and original values
by chromosome with lines

24. Example of genetic effects and original values
by chromosome with symbols

25. Features
• The Y2 axis can be used to display a variable
unrelated to P-values such as minor allele frequency
or allele frequency difference between the best and
worst individuals, allowing the production of more
flexible and informative graphs than using Y1 axis
presenting P-values only.
• Option to select traits to display, to customize the
color of each trait or switch Y1 and Y2 axes so that
chromosome graphs may not be crowded .
• Each Y axis, Y1 or Y2, can have its own threshold P-
value or cut-off P-value

26. A chromosome graph with two threshold value lines for Y1 and Y2 axes, and
elimination of P-values below the line of cut-off P-value line.
Wang et al. BMC Bioinformatics 2012 13:319

27. INPUT/OUTPUT
• SNPEVG2 requires a simple text input file with
the same format as for SNPEVG1, i.e., CHR,
POSITION, SNP, and P-VALUE columns.
• OUTPUT: .png files

28. The SNPEVG Convert Program
• The SNPEVGconvert program is designed to
convert an output file from any GWAS analysis
software to the format of SNPEVG1 and
SNPEVG2.
• To use this program, the user only needs to
specify the number of columns in the original
files and identify the column numbers to be
printed in the input file for SNPEVG1 and
SNPEVG2.

29. Example of the parameter file for
SNPEVGconvert
• plink.assoc.linear # input file name
• 5 # number of columns in the output file
• 2 1 3 9 8 # positions of columns to print as input
file for SNPEVG1 and SNPEVG2
• assoc.snpe # output file name

30. The SNPEVG3 program
• SNPEVG3 is developed for graphical analysis of GWAS
using the output file of single-locus test results of EPISNP
or EPISNPmpi as the input file for drawing figures.
• SNPEVG3 has similar GUI features as SNPEVG1, but it
does not have the limit of 100 traits.
• This program draws graphs for P-values of additive,
dominance and genotypic effects on the Y1 axis and draws
sample size on the Y2 axis.
• The P-values can be displayed with lines connecting
adjacent data points or use symbols without connecting
lines.
• The user has an option to draw a figure by a sorted effect
such as additive or dominance effect.

31. INPUT FILE FORMAT
Trait Chr Locus M A D #_Ind
Trait1 14 M112 0.704E+00 0.107E+01 0.285E+00 295
Trait2 14 M112 0.492E+00 0.127E+00 0.864E+00 295
trait1 14 M212 0.401E+00 0.689E-01 0.748E+00 295
trait1 19 M7 0.184E+01 0.180E+01 0.803E+00 290
M= Name of marker
# ind = No of individuals with this trait.

32. Chromosome figure of SNPEVG3 with connecting line between adjacent data points.

33. Chromosome figure of SNPEVG3 without
connecting line between adjacent data points.

34. REFERENCES
• Wang et al. “SNPEVG: a graphical tool for
GWAS graphing with mouse clicks”, BMC
Bioinformatics, 2012 13:319
doi:10.1186/1471-2105-13-319
• http://www.biomedcentral.com/content/sup
plementary/1471-2105-13-319-s3.pdf