LocusZoom is designed to facilitate viewing of local association results together with useful information about a locus, such as the location and orientation of the genes it includes, linkage disequilibrium coefficients and local estimates of recombination rates. It was developed by popular demand, as a result of many questions we have had about "How did you make the figures in your talk?" or "How did you make the figures for your GWAS paper?" (And for better or for worse, we have quite a few GWAS papers!!).
LocusZoom can be used in three ways:
- Plot Summaries of Your Genomewide Scan Interactively
- You can upload summary results of your own genomewide scan or genomewide meta-analysis and request plots of regions of interest using a web-based form.
- Generate Many Plots in Batch Mode
- You can upload summary results for your genomewide scan or genomewide meta-analysis and request several plots in one go by uploading a batch file. You will receive results via e-mail. A snail-mail option is not available.
- Plot Summaries of Publicly Available Datasets
- Currently, this includes the results of our genome-wide scan for variants associated with HDL-cholesterol, LDL-cholesterol and triglyceride levels in ~20,000 individuals.
We are also developing a distributable code package that you can install on your own system to generate plots locally. This is not yet available, but is expected in April 2010.
- 1 Upload your own meta-analysis file and generate single plots using a web-based form
- 2 Using Batch Mode
- 3 Generate single plots using our publicly-available lipids GWAS data
- 4 Commonly Used LocusZoom Options
Upload your own meta-analysis file and generate single plots using a web-based form
Uploading Your Association Study Results
Association results can be uploaded to our web server using the plot your data webpage. Result files are limited to 20Mb in size, which allows for a gzipped text table including key columns (marker name, p-value and sample size) for up to ~3 million SNPs. In our tests, a typical GWAS results file is ~17 Mb in size after imputation of HapMap SNPs. Once a file is uploaded, LocusZoom will remember the file for the duration of your web session allowing you to generate multiple plots. If you have a slow connection or would like to save time, you can upload results for a region or chromosome of interest only. Your results are entirely confidential and won't be viewed by us or anyone else (except those with whom you share them!)
To specify the region to be plotted, you will have to specify the name of a key marker in the region (typically, as an rs-number), name a gene of interest or provide appropriate genome coordinates. When displaying linkage disequilibrium, plotting will be very fast for small windows when HapMap CEU linkage disequilibrium is requested (because pairwise coefficients have been precomputed) and will be a bit slower for larger windows (because linkage disequilibrium coefficients must be computed on the fly).
If you include a sample size column in the result file, it will be used to control the size of each plotted marker.
Plotting of Pairwise Linkage Disequilibrium
In the main plot window, data points are colored according to their level of linkage disequilibrium (LD) of the each SNP with the index SNP. If users specify the region to display using an index SNP and flanking region, LD of all data points will be relative to the user-specified index SNP. If users specify the region to display using genome coordinates or a gene name, LocusZoom will automatically select the most significant SNP in the region as the index SNP. For all other SNPs in the plot, the color of the data point will reflect the pairwise LD with this index SNP. The default LD measure is r2 calculated from the HapMap CEU population (release 22), but users have the option to replace this with D’ and of selecting the HapMap YRI, Hapmap CHB+JPT or 1000 Genomes CEU reference panels. Because we have pre-computed LD for all SNPs in HapMap CEU, plots will often generate more quickly if using the default LD information. SNPs with missing LD information are shown in grey.
Customizing the Display of Your Results
All options listed in the Main Table above are available, as well as the options listed below
|Column Delimiter||none||Users must specify the type of column delimiter in the results file|
|Pvalue Column Name||none||Users must specify the name of the column that contains the p-values|
|Marker Column Name||none||Users must specify the heading of the column that contains marker names|
|Human Genome Build||none||Plots can be generated based on hg18 (default) or hg17 positions|
|HapMap Population for LD||none||This option allows the user to specify which HapMap population was used to obtain LD estimates. The default is CEU but users may select YRI or JPT+CHB|
Using Batch Mode
To start batch mode, first upload your results file just as you would in interactive mode. The same file size restrictions apply.
Generating a Hit Spec File
Batch mode allows you to conveniently specify a set of plots to be generated in "Hit Spec" file. This is handy if you need to generate large numbers of plots or if you want to plot the same set of regions after updating a genomewide analysis (for example).
The "Hit Spec" file is a whitespace delimited text file. The file has six mandatory columns which can be followed by a series of optional key=value pairs to allow for detailed customization of each plot. The first line in the file is assumed to be a header and is ignored. Each subsequent line describes a single plot. There are three ways to select a region to plot:
- Plotting a window flanking an interesting SNP
- This option allows you to plot results for all markers within a specific distance (e.g. 500kb) of an index SNP. To use this option, set column 1 to have the name of the index SNP (e.g. rs2 below) and set column 5 to specify the width of the region of interest (e.g. 500kb below). Here is an example:
Feature chr start end flank plot arguments rs1 na na na 500kb yes rfrows=3 weightCol=”N” snpset=”HapMap” metalRug=”Our SNPs”
- Plotting a region flanking an interesting SNP
- This option is similar to the previous option, but allows you to specify an assymetric region of interest. For example, perhaps you interested in a plot that extends a bit further to the right of the SNP of interest. In this case, specify the coordinates of the region to be plotted in columns 2, 3, and 4. Here is an example:
Feature chr start end flank plot arguments rs2 1 540000 580000 na yes rfrows=4 legend=”right” showAnnot=T
- Plotting a region flanking a gene of interest
- This option allows you to focus on a particular gene, rather than a specific SNP. It is similar to the first option. You should set column 1 to be the name of the gene of interest and column 5 to be the desired window width. When you use this option, LocusZoom will automatically select an index SNP for each region; the SNP will be the site with the smallest p-value. Here is an example:
Feature chr start end flank plot arguments CETP na na na 200kb yes rfrows=6 showAnnot=T annotPch=”1,24,24,25,22,21,8,7”
The sixth column in the "Hit Spec" file can be used to enable (with the value yes) or disable (with the value no) an individual plot. For example, if you run a "Hit Spec" file with 15 plots and 14 of them turn out very nicely, you may wish to re-run the "Hit Spec" file with some tweaks to the problem plot. In this case (if you dislike waiting for your results as much as we do!), you could disable generation of the plots that seem nice by changing the 6th column to “no” and leave the plot that you tweaked as a “yes”.
The 7th and final column contains additional LocusZoom arguments as key=value pairs. Any number of key=value pair arguments can be included. For details of available options, see the section entitled LocusZoom options below.
Generate single plots using our publicly-available lipids GWAS data
In addition to plotting your own results, you can plot the results of some publicly available GWAS. Currently, the only publicly available set of results is our GWAS for loci determining blood lipid levels (Kathiresan et al, Nature Genetics 2009). Just like when you are plotting your own data, you can specify 1) an index SNP and a flanking region, 2) the chromosome together with start and stop positions (in basepairs), or 3) gene name and a flanking region.
Commonly Used LocusZoom Options
|Web Form||"Hit Spec" File Key-Value Pair||Description|
|Title on Plot||title=”My Favorite Locus”||Specifies large text displayed above the plot|
|Human Genome Build||n/a||Plots can be generated based on hg18 (the default) or hg17 positions|
|Legend Location||legend=”left”||This specifies the location of the legend within the plot, the default is auto. Auto tries to select a location that overlaps a minimal number of datapoints. (auto, left, right, none)|
|SNP Position Rug||snpset=”HapMap” metalRug=”Rug SNPs”||These options control display of tickmarks indicating SNP positions at the top of the plot. Setting snpset="HapMap", snpset="Illu318" or snpset="Affy500" display a fixed set of SNPs. (You can also try snpset="Affy500,Illu318,HapMap" to see all 3). The metalRug option displays a rug which only includes the SNPs that are actually plotted. To remove the rug in batch mode set snpset=NULL.|
|Number of Rows for Gene Names||rfrows=4||LocusZoom will automatically tries to determine the number of display rows to use for genes and gene names so they are not overlapping. This can make each plot prettier, but is not ideal when you want to compare many plots side by side. To ensure a fixed amount of space is used for gene names, use this option to set the maximum number of display rows. If LocusZoom runs out of plotting space and some genes are left out, a warning will be added to the plot.|
|Point Size||weightCol=”SampleSize”||This specifies that the “dot size” of each data points will reflect the square-root of the sample size. The default is to have all dot sizes equal.|
|LD Measure||ldCol=”dprime” (“rsquare”)||Colors data points according to the selected LD measure. The default is "rsquare".|
|Reference Population for LD||n/a||This option allows the user to specify which reference panel is used to obtain LD estimates. The default is CEU from HapMap Phase II but users may select YRI or JPT+CHB from HapMap Phase II, or CEU from 1000 Genomes (August 2009 release).|
|Highlight Region of Interest||hiStart=425Mb hiEnd=425.1Mb||A grey box can be used to highlight important regions of the genome – this can reflect where an association signal peaks or a region selected for sequencing, for example.|
|Theme||theme=”publication”||We have created a theme that has larger text and is more easily readable for publication.|
|Show Annotation||showAnnot=T showRefsnpAnnot=T annotPch=”21,24,24,25,22,22,8,7”||SNP annotation is available for all 1000G SNPs (Aug 2009 release) and can be enabled with the showAnnot=T option. The annotPch command allows you to customize the R plotting symbol used for each kind of SNP; it is okay to use the same symbol for more than one category. The annotation categories, together with their default symbol setting are: Framestop (24, triangle), Splice (24, triangle), NonSynonymous (25, inverted triangle), Synonymous (22, square), UTR (22, square), TFBScons (8, star), MCS44 Placental (7, square with diagonal lines) and None-of-the-above (21, filled circle). For more information about these annotation categories used, please see http://research.nhgri.nih.gov/tools/unisnp/?rm=ohelp|
|Recombination Rate Overlay||showRecomb=T||The estimated recombination rate from HapMap samples can be shown on the plot or left off. The data plotted are from Hapmap; http://hapmap.ncbi.nlm.nih.gov/downloads/recombination/2008-03_rel22_B36/rates/|