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| − | {| align="right"
| + | #REDIRECT [[LocusZoom_Standalone]] |
| − | |-
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| − | | __TOC__
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| − | |}
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| − | | |
| − | <br> [[Image:LocusZoomSmall.png]]
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| − | | |
| − | This page contains information regarding a version of LocusZoom that may be downloaded for personal use. For more information on LocusZoom, see this [[LocusZoom|page]].
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| − | | |
| − | To be notified of future changes to LocusZoom, you can join our [http://groups.google.com/group/locuszoom Google Group].
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| − | | |
| − | == Quick Start (Requirements) ==
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| − | | |
| − | The following software is required:
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| − | | |
| − | *[http://www.python.org/download/ Python 2.6] (do '''not''' download the 3.0 branch!)
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| − | *[http://www.r-project.org/ R 2.10+]
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| − | | |
| − | | |
| − | The following software is optional but recommended:
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| − | | |
| − | *[[New Fugue|new_fugue]], a program for computing LD, written by Goncalo Abecasis.
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| − | *[http://pngu.mgh.harvard.edu/~purcell/plink/ PLINK], written by Shaun Purcell.
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| − | | |
| − | | |
| − | The following R packages are optional but recommended:
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| − | *[http://cran.r-project.org/web/packages/gridExtra/index.html gridExtra] (used for creating summary tables of GWAS hits / fine-mapping SNPs as additional pages in the PDF)
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| − | | |
| − | | |
| − | For the latest stable LocusZoom package, see our [https://statgen.sph.umich.edu/locuszoom/download/ download] page. The current version is '''1.2''', released on May 10th, 2013.
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| − | | |
| − | Currently only '''Unix/Linux''' is supported, though Mac OS X should be supported in a future release. Support for Windows may come at a much later date.
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| − | | |
| − | == Synopsis ==
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| − | | |
| − | First, change directory into examples/. Then, run the following command:
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| − | <pre>./run_example.py</pre>
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| − | This script runs the following command for you:
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| − | <pre>../bin/locuszoom --metal Kathiresan_2009_HDL.txt --refgene FADS1</pre>
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| − | A PDF plot of the FADS1 locus will be created in the directory. It should look roughly like this:
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| − | | |
| − | [[Image:FADS1 small.png]]
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| − | | |
| − | == Download ==
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| − | | |
| − | See our [https://statgen.sph.umich.edu/locuszoom/download/ download] page for links to the latest as well as previous releases.
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| − | | |
| − | == Changes in Version 1.2 ==
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| − | | |
| − | A number of new features have been added for this version. See the following sections for more info:
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| − | | |
| − | * [[#EPACTS formatted file|Loading EPACTS results]]
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| − | * [[#Plotting LD with additional reference SNPs|Plotting LD with additional reference SNPs]]
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| − | * [[#Labeling multiple SNPs|Labeling multiple SNPs]]
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| − | * [[#Fine-mapping credible sets|Fine-mapping credible sets]]
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| − | * [[#GWAS catalog variants|GWAS catalog variants]]
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| − | * [[#Supply VCF files for calculating LD|Supply VCF files for calculating LD]]
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| − | | |
| − | | |
| − | The full changelog is available on the [https://statgen.sph.umich.edu/locuszoom/download/ download] site.
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| − | | |
| − | == Installation ==
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| − | | |
| − | === Step 1: Install Python ===
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| − | | |
| − | You will need to install Python on your system if it is not already. Head over to [http://www.python.org www.python.org] to download it. Note that you will want to make sure to download the latest from the 2.x branch, and <span style="color:#ff0000">'''*not*'''</span> the 3.x one.
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| − | | |
| − | === Step 2: Install R ===
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| − | | |
| − | R is also required for generating the plots. You can download R at [http://www.r-project.org/ www.r-project.org]. Version 2.10 or greater is required.
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| − | | |
| − | === Step 3: Install LD calculation software (optional) ===
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| − | | |
| − | * If you wish to calculate from hg18 sources (hapmap, earlier releases of 1000G): install '''new_fugue''' (see below.)
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| − | * If you wish to calculate from hg19 sources (latest 1000G): install '''PLINK''' (see below.)
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| − | * If you plan to supply your own LD files per region, or calculate LD directly from VCF files: install nothing! See options for --ld and --ld-vcf.
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| − | | |
| − | ==== new_fugue ====
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| − | | |
| − | New_fugue is a program that calculates linkage disequilibrium measures from genotype files. While installing new_fugue is optional, we highly recommend it as it makes the process of generating plots much easier. If you opt to skip installing new_fugue, you will need to provide your own computed LD files for each region that you want to plot.
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| − | | |
| − | New_fugue can be downloaded from [[New Fugue|here]].
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| − | | |
| − | Once downloaded, extract the tar file using:
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| − | <pre> tar zxf /path/to/new_fugue.tar.gz</pre>
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| − | Change into the generic-new_fugue directory that is created, and run:
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| − | <pre> make install </pre>
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| − | | |
| − | You may need administrator rights to install this program.
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| − | | |
| − | ==== PLINK ====
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| − | | |
| − | PLINK is now used to calculate LD for all future LD sources / populations that we may add. The program new_fugue (above) is used to calculate LD from older sources (such as hapmap) and older builds (such as hg18) where LD files are sufficiently small.
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| − | | |
| − | You can download PLINK and find instructions for installing it [http://pngu.mgh.harvard.edu/~purcell/plink/download.shtml here].
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| − | | |
| − | === Step 5: Install LocusZoom ===
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| − | | |
| − | LocusZoom is provided as a tar archive which contains the following:
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| − | | |
| − | *the LocusZoom python application
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| − | *the R script used for generating plots
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| − | *Human genome '''build hg18 and hg19''' data, including:
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| − | **genotype files (used for computing LD) from HapMap and 1000G
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| − | **a SQLite database file containing tables describing SNP positions, SNP annotations, gene and exon locations, and recombination rates
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| − | | |
| − | Simply unpack the tar to your directory of choice by doing the following:
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| − | <pre>cd <directory where you want to place locuszoom>
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| − | tar zxf /path/to/locuszoom.tgz
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| − | </pre>
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| − | The tar archive will extract into the following directory structure:
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| − | | |
| − | *locuszoom/
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| − | **bin/
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| − | ***locuszoom (this is the locuszoom "executable")
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| − | ***locuszoom.R (the R script which is used by locuszoom for creating the plots)
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| − | **conf/ (configuration file located here)
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| − | **data/
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| − | ***database/ (SQLite file located here)
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| − | ***hapmap/ (hapmap genotype files)
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| − | ***1000G/ (1000G genotype files)
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| − | **src/ (source code for locuszoom)
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| − | | |
| − | It is important that this directory structure remain intact. To make launching locusoom easier, you could create a link to it from /usr/local/bin, for example:
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| − | <pre>ln -s bin/locuszoom /usr/local/bin/locuszoom</pre>
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| − | | |
| − | == Sources of information ==
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| − | | |
| − | LocusZoom uses various sources of information for annotation, positions, and calculating LD.
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| − | | |
| − | For computing LD:
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| − | *[ftp://ftp.hapmap.org/hapmap/genotypes/2008-10_phaseII/ HapMap genotypes] for populations CEU, YRI, and JPT+CHB.
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| − | *[ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/pilot_data/release/2010_03/pilot1 1000 Genomes genotypes]
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| − | | |
| − | For SNP, gene, and exon positions:
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| − | *[http://www.ncbi.nlm.nih.gov/projects/SNP/ dbSNP position] via the [http://genome.ucsc.edu UCSC Genome Browser]
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| − | *[http://www.ncbi.nlm.nih.gov/RefSeq/ Gene and exon positions] via the [http://genome.ucsc.edu UCSC Genome Browser]. We filtered SNPs that map to more than one location or where no allele matches the reference sequence.
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| − | | |
| − | For annotation:
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| − | *We use various sources including RefSeq Genes (refFlat), TFBS Conserved (tfbsConsSites), and Conservation (phaseConsElements44wayPlacental), all available from the [http://genome.usc.edu UCSC Genome Browser].
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| − | *[ftp://ftp.hapmap.org/hapmap/recombination/2008-03_rel22_B36/rates/ Recombination rates from HapMap].
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| − | | |
| − | For GWAS hits:
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| − | *We use the NHGRI GWAS catalog, available at [http://www.genome.gov/gwastudies/ genome.gov]
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| − | | |
| − | == Input ==
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| − | | |
| − | === Association results file ===
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| − | | |
| − | LocusZoom requires an association results file similar in formatting to what METAL or EPACTS provides.
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| − | | |
| − | ==== METAL formatted file ====
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| − | | |
| − | The file must have 2 columns: markers (SNPs), and p-values. The file should look something like this:
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| − | | |
| − | <br>
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| − | | |
| − | {| width="25%" cellspacing="0" cellpadding="1" border="1"
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| − | |-
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| − | ! scope="col" | MarkerName
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| − | ! scope="col" | P-value
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| − | |-
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| − | | align="center" | rs1
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| − | | align="center" | 0.423
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| − | |-
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| − | | align="center" | rs2
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| − | | align="center" | 1.23e-04
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| − | |-
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| − | | align="center" | rs3
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| − | | align="center" | 9.4e-390
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| − | |}
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| − | | |
| − | <br>
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| − | | |
| − | This file should be passed to locuszoom using the <code>--metal</code> option.
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| − | | |
| − | The file should be tab-delimited, though this can be changed using the <code>--delim </code> option.
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| − | | |
| − | If your marker and p-value column names are not "MarkerName" and "P-value", you may set them with <code>--markercol</code> and <code>--pvalcol</code> options.
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| − | | |
| − | P-values of any magnitude are supported in scientific notation (we use an arbitrary precision library built-in to python, and transform p-values to the log scale.) If you've already transformed your p-values to the log scale, simply use <code>--no-transform</code> and LocusZoom will not transform them.
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| − | | |
| − | ==== EPACTS formatted file ====
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| − | | |
| − | The file can come directly from [[EPACTS]], or simply be formatted similarly to the following:
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| − | | |
| − | {|
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| − | |-
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| − | ! scope="col" | #CHROM
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| − | ! scope="col" | BEGIN
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| − | ! scope="col" | END
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| − | ! scope="col" | MARKER_ID
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| − | ! scope="col" | NS
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| − | ! scope="col" | AC
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| − | ! scope="col" | CALLRATE
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| − | ! scope="col" | MAF
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| − | ! scope="col" | PVALUE
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| − | ! scope="col" | SCORE
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| − | ! scope="col" | N.CASE
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| − | ! scope="col" | N.CTRL
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| − | ! scope="col" | AF.CASE
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| − | ! scope="col" | AF.CTRL
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| − | |-
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| − | | 1 || 15903 || 15903 || 1:15903_G/GC || 2657 || 3892.2 || 1 || 0.26757 || 0.36771 || 0.90077 || 1326 || 1331 || 1.4688 || 1.4609
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| − | |-
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| − | | 1 || 19190 || 19191 || 1:19190_GC/G || 2657 || 823.65 || 1 || 0.155 || 0.67173 || 0.42378 || 1326 || 1331 || 0.3115 || 0.30849
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| − | |-
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| − | | 1 || 20316 || 20317 || 1:20316_GA/G || 2657 || 1005.3 || 1 || 0.18917 || 0.50804 || 0.66189 || 1326 || 1331 || 0.38062 || 0.37607
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| − | |-
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| − | | 1 || 30967 || 30970 || 1:30967_CCCA/C || 2657 || 435.35 || 1 || 0.081925 || 0.08848 || -1.7035 || 1326 || 1331 || 0.16007 || 0.16762
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| − | |-
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| − | | 1 || 51972 || 51975 || 1:51972_GGAC/G || 2657 || 207.8 || 1 || 0.039104 || 0.51638 || -0.64893 || 1326 || 1331 || 0.077187 || 0.079226
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| − | |-
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| − | | 1 || 53138 || 53140 || 1:53138_TAA/T || 2657 || 216.2 || 1 || 0.040685 || 0.55679 || 0.58762 || 1326 || 1331 || 0.083145 || 0.079602
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| − | |-
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| − | | 1 || 54421 || 54421 || 1:54421_A/G || 2657 || 179.45 || 1 || 0.033769 || 0.73592 || 0.33726 || 1326 || 1331 || 0.068213 || 0.066867
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| − | |-
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| − | | 1 || 66221 || 66221 || 1:66221_A/AT || 2657 || 664.45 || 1 || 0.12504 || 0.48676 || 0.69547 || 1326 || 1331 || 0.25366 || 0.24651
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| − | |-
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| − | | 1 || 66222 || 66223 || 1:66222_TA/T || 2657 || 470.3 || 1 || 0.088502 || 0.64258 || 0.4641 || 1326 || 1331 || 0.17941 || 0.17461
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| − | |-
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| − | |}
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| − | | |
| − | The chrom, start, end, marker ID, and p-value columns must all be present. The file must be tab-delimited.
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| − | | |
| − | To load this file, use --epacts.
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| − | | |
| − | === Region ===
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| − | | |
| − | You can specify the region to plot in any one of the following ways:
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| − | | |
| − | *A reference SNP and flanking region
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| − | <pre> --refsnp <your snp> --flank 500kb </pre>
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| − | | |
| − | *A reference SNP and chromosome/start/stop specification
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| − | <pre> --refsnp <your snp> --chr # --start <base position> --end <base position> </pre>
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| − | | |
| − | *A reference SNP and gene:
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| − | <pre> --refsnp <your snp> --refgene <your gene> </pre>
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| − | | |
| − | This will use the reference gene as the plotting boundaries. You can extend the boundaries by also including --flank.
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| − | | |
| − | *A gene and flanking region
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| − | <pre> --refgene <your gene> --flank 250kb </pre>
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| − | The flank is computed as +/- from the transcription start/end of the gene. From this region, LocusZoom will find the SNP with the most significant p-value, and use this as the reference SNP.
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| − | | |
| − | *A gene and chromosome/start/stop specification
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| − | <pre> --refgene <your gene> --chr # --start <base position> --end <base position> </pre>
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| − | This method is similar to the above, except that an exact region is specified. LD with the SNP with the most significant p-value in this region will be used to color data points.
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| − | | |
| − | *A chromosome/start/stop specification
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| − | <pre> --chr # --start <base position> --end <base position> </pre>
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| − | The SNP with the most significant p-value in this region will be used for estimating LD.
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| − | | |
| − | === Specifying LD source/population/build ===
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| − | | |
| − | We supply genotype files for computing LD between the reference SNP and all other SNPs within the region you are plotting. The tables below show the supported combinations of LD source, population, and build. Note that you can always provide your own LD files, see [[#User-supplied_LD|User-supplied LD]] for more information.
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| − | | |
| − | '''1000G'''
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| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1"
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| − | |-
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| − | ! align="left" scope="col" | Release
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| − | ! align="left" scope="col" | Build
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| − | ! align="left" scope="col" | Population
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| − | ! align="left" scope="col" | LocusZoom Arguments
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| − | |-
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| − | | March 2012
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| − | | hg19
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| − | | ASN
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| − | | --pop ASN --build hg19 --source 1000G_March2012
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| − | |-
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| − | | March 2012
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| − | | hg19
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| − | | AFR
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| − | | --pop AFR--build hg19 --source 1000G_March2012
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| − | |-
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| − | | March 2012
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| − | | hg19
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| − | | EUR
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| − | | --pop EUR --build hg19 --source 1000G_March2012
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| − | |-
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| − | | March 2012
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| − | | hg19
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| − | | AMR
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| − | | --pop AMR --build hg19 --source 1000G_March2012
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| − | |-
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| − | | Nov 2010
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| − | | hg19
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| − | | ASN
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| − | | --pop ASN --build hg19 --source 1000G_Nov2010
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| − | |-
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| − | | Nov 2010
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| − | | hg19
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| − | | AFR
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| − | | --pop AFR --build hg19 --source 1000G_Nov2010
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| − | |-
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| − | | Nov 2010
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| − | | hg19
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| − | | EUR
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| − | | --pop EUR --build hg19 --source 1000G_Nov2010
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| − | |-
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| − | | June 2010
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| − | | hg18
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| − | | CEU
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| − | | --pop CEU --build hg18 --source 1000G_June2010
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| − | |-
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| − | | June 2010
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| − | | hg18
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| − | | YRI
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| − | | --pop YRI --build hg18 --source 1000G_June2010
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| − | |-
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| − | | June 2010
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| − | | hg18
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| − | | JPT+CHB
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| − | | --pop JPT+CHB --build hg18 --source 1000G_June2010
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| − | |-
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| − | | August 2009
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| − | | hg18
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| − | | CEU
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| − | | --pop CEU --build hg18 --source 1000G_Aug2009
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| − | |-
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| − | | August 2009
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| − | | hg18
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| − | | YRI
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| − | | --pop YRI --build hg18 --source 1000G_Aug2009
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| − | |-
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| − | | August 2009
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| − | | hg18
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| − | | JPT+CHB
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| − | | --pop JPT+CHB --build hg18 --source 1000G_Aug2009
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| − | |}
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| − | | |
| − | <br> '''HapMap Phase II'''
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| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1"
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| − | |-
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| − | ! align="left" scope="col" | Build
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| − | ! align="left" scope="col" | Population
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| − | ! align="left" scope="col" | LocusZoom Arguments
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| − | |-
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| − | | hg18
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| − | | CEU
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| − | | --pop CEU --build hg18 --source hapmap
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| − | |-
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| − | | hg18
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| − | | YRI
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| − | | --pop YRI--build hg18 --source hapmap
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| − | |-
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| − | | hg18
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| − | | JPT+CHB
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| − | | --pop JPT+CHB --build hg18 --source hapmap
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| − | |}
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| − | | |
| − | | |
| − | === Batch mode ===
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| − | | |
| − | LocusZoom provides a batch mode for generating plots for a large number of regions:
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| − | | |
| − | *<code>--hitspec </code>, which reads a batch mode specification file.
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| − | | |
| − | For this option, you must provide a text file of the following format:
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| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1"
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| − | |-
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| − | ! scope="col" | Column
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| − | ! scope="col" | Description
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| − | |-
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| − | | snp
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| − | | Can be either a SNP, or gene.
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| − | |-
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| − | | chr
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| − | | Chromosome
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| − | |-
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| − | | start
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| − | | Start position to display on plot.
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| − | |-
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| − | | end
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| − | | End position to display on plot.
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| − | |-
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| − | | flank
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| − | | Flank for region. Can be given instead of chr/start/stop.
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| − | |-
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| − | | run
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| − | | Should this row be read? Should be "yes" or "no".
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| − | |-
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| − | | m2zargs
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| − | | List of arguments for customizing plots. You can find a list of them here: [[LocusZoom#Commonly_Used_LocusZoom_Options|Commonly Used LocusZoom Options]]
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| − | |}
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| − | | |
| − | <br>
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| − | | |
| − | The file should be delimited by whitespace (tab, space, multiple spaces), and the header must exist, with column names exactly as specified in the table above. As an example, consider the following file:
| |
| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1" class="sortable"
| |
| − | |-
| |
| − | ! scope="col" | snp
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| − | ! scope="col" | chr
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| − | ! scope="col" | start
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| − | ! scope="col" | stop
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| − | ! scope="col" | flank
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| − | ! scope="col" | run
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| − | ! scope="col" | m2zargs
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| − | |-
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| − | | rs7983146
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| − | | NA
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| − | | NA
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| − | | NA
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| − | | 500kb
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| − | | yes
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| − | | title="My favorite SNP"
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| − | |-
| |
| − | | TCF7L2
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| − | | NA
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| − | | NA
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| − | | NA
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| − | | 1.25MB
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| − | | yes
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| − | | title="TCF7L2 Region" showRecomb=F
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| − | |-
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| − | | rs7957197
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| − | | 12
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| − | | 119503590
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| − | | 120322280
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| − | | NA
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| − | | yes
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| − | | showAnnot=F
| |
| − | |}
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| − | | |
| − | <br>
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| − | | |
| − | The first row would plot rs7983146 as the reference SNP, and a region of 500kb on either side of it. The plot title would read "My favorite SNP."
| |
| − | | |
| − | The second row would plot 1.25 MB on either side of TCF7L2's transcription start and stop. The SNP with the most significant p-value in your <code>--metal</code> file will be used as the reference SNP. The plot title would read "TCF7L2 Region", and the recombination overlay would be disabled using showRecomb=F.
| |
| − | | |
| − | The third row would plot rs7957197 as the reference SNP, but here we've specifically designated the region to plot, which is chr12:119503590-120322280. We've also disabled showing SNP annotations with showAnnot=F.
| |
| − | | |
| − | === User-supplied LD ===
| |
| − | | |
| − | If new_fugue is installed, LocusZoom will automatically compute LD between the reference SNP and all other SNPs within each region to be plotted. However, you may wish to provide your own file with LD information. This can be done with the <code>--ld</code> option, which requires a file of the following format:
| |
| − | | |
| − | <br>
| |
| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | Column
| |
| − | ! scope="col" | Description
| |
| − | |-
| |
| − | | snp1
| |
| − | | Any SNP in your plotting region.
| |
| − | |-
| |
| − | | snp2
| |
| − | | Should always be the reference SNP in the region.
| |
| − | |-
| |
| − | | dprime
| |
| − | | D' between snp2 (reference SNP) and snp1.
| |
| − | |-
| |
| − | | rsquare
| |
| − | | r<sup>2</sup> between snp2 (reference SNP) and snp1.
| |
| − | |}
| |
| − | | |
| − | <br>
| |
| − | | |
| − | The dprime column can be all missing if it is not known. Rsquare must be present, and must be valid data.
| |
| − | | |
| − | The file should be whitespace delimited, and the header (column names shown above) must exist.
| |
| − | | |
| − | === Supply VCF files for calculating LD ===
| |
| − | | |
| − | You can give LocusZoom a VCF file directly to use for calculating LD:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | locuszoom --ld-vcf my_genotypes.vcf.gz ...
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | This option takes the place of having to supply per-region pre-calculated LD (--ld) or having to specify --pop and --source for calculating LD from genotype files supplied by LZ.
| |
| − | | |
| − | <span style="color:#FF6600">'''Warning: '''</span> The VCF file must also have a [http://samtools.sourceforge.net/tabix.shtml tabix] index located in the same directory. For the above example, the tabix index "my_genotypes.vcf.gz.tbi" must exist.
| |
| − | | |
| − | | |
| − | You can also calculate D' from phased VCF files:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | locuszoom --ld-vcf my_genotypes.vcf.gz --ld-measure dprime ...
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | The default measure is "rsquared".
| |
| − | | |
| − | == Optional Input ==
| |
| − | | |
| − | === Plotting LD with additional reference SNPs ===
| |
| − | | |
| − | LocusZoom can now show LD with multiple SNPs in a region (for example, you might want to show LD with a number of SNPs from a conditional analysis.)
| |
| − | | |
| − | You give LocusZoom the usual reference SNP (used for centering the plot and calculating the region) but an additional set of lead/reference SNPs as well.
| |
| − | | |
| − | For all other SNPs not in the "lead SNP set" of { reference SNP, additional reference SNPs }, LZ will find which of the lead SNPs it is in highest LD with, and color it to match that lead SNP. The extent of LD with the lead SNP is shown by a gradient of color.
| |
| − | | |
| − | | |
| − | As an example:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | locuszoom --metal <DIAGRAM T2D results> --refsnp "rs231362" --add-refsnps "rs163184"
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | Will generate the following plot:
| |
| − | | |
| − | [[File:New lz cond only.png|700px]]
| |
| − | | |
| − | | |
| − | The following options are available for changing the style of these types of plots:
| |
| − | | |
| − | {| width="85%" cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | Option (with default value)
| |
| − | ! scope="col" | Description
| |
| − | |-
| |
| − | | condLdColors="gray60,#E41A1C,#377EB8,#4DAF4A,#984EA3,#FF7F00,#A65628,#F781BF"
| |
| − | | First color is missing LD color, the rest are used as needed for each additional lead SNP
| |
| − | |-
| |
| − | | drawMarkerNames = T
| |
| − | | Display marker names (or not) above lead SNPs
| |
| − | |-
| |
| − | | condLdLow=NULL
| |
| − | | Used to set all SNPs with LD in the lowest bin to the same color, for example condLdLow="gray70"
| |
| − | |-
| |
| − | | condRefsnpPch=23
| |
| − | | Symbol for each lead SNP, defaults to diamond
| |
| − | |-
| |
| − | | condPch='4,16,17,15,25,8,7,13,12,9,10'
| |
| − | | Plotting symbols for groups of SNPs in LD with additional refsnps, make sure they don't overlap with condRefsnpPch above
| |
| − | |-
| |
| − | | ldCuts = "0,.2,.4,.6,.8,1"
| |
| − | | Bins for LD
| |
| − | |}
| |
| − | | |
| − | === GWAS catalog variants ===
| |
| − | | |
| − | You can add known GWAS variants to your plots with the following:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | lzdev --gwas-cat whole_cat-significant-only --build hg19 ...
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | [[File:New lz gwas cat.png|900px]]
| |
| − | | |
| − | | |
| − | Currently the only catalog is the NHGRI GWAS catalog from [http://www.genome.gov/gwastudies/ genome.gov].
| |
| − | | |
| − | <pre>
| |
| − | Available GWAS catalogs for build hg19:
| |
| − | | |
| − | +----------------------------+----------------------------------------------------------------+
| |
| − | | Option | Description |
| |
| − | +----------------------------+----------------------------------------------------------------+
| |
| − | | whole-cat_significant-only | The entire GWAS catalog, filtered to SNPs with p-value < 5E-08 |
| |
| − | +----------------------------+----------------------------------------------------------------+
| |
| − | </pre>
| |
| − | | |
| − | | |
| − | If the R package '''gridExtra''' is installed, a summary of each GWAS catalog variant in your region is listed later in the PDF:
| |
| − | | |
| − | [[File:New lz gwas summary.png|500px]]
| |
| − | | |
| − | === Fine-mapping credible sets ===
| |
| − | | |
| − | LocusZoom can add an additional track to the plot showing results from a fine-mapping analysis. These are typically SNPs within the 95% credible set (see [http://www.nature.com/ng/journal/v44/n12/full/ng.2435.html this paper] for an example.)
| |
| − | | |
| − | To add this fine-mapping track, you supply (as a plotting option) the fine-mapping set of credible SNPs as a file:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | locuszoom ... fineMap="my_finemapping_results.txt"
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | | |
| − | The fine-mapping results file should be a tab-delimited file with each fine-mapping SNP (for example, all those fine-mapping SNPs in the 95% credible set), a descriptive label (EUR/AMR/AFR/etc.), and a color:
| |
| − | | |
| − | {| class="wikitable sortable"
| |
| − | |-
| |
| − | ! scope="col" | snp
| |
| − | ! scope="col" | chr
| |
| − | ! scope="col" | pos
| |
| − | ! scope="col" | pp
| |
| − | ! scope="col" | group
| |
| − | ! scope="col" | color
| |
| − | |-
| |
| − | | rs1 || 18 || 55931115 || 0.88 || AMR || red
| |
| − | |-
| |
| − | | rs1 || 18 || 55920115 || 0.88 || AMR || red
| |
| − | |-
| |
| − | | rs1 || 18 || 55940115 || 0.88 || AMR || red
| |
| − | |-
| |
| − | | rs1 || 18 || 55930115 || 0.88 || EUR || blue
| |
| − | |-
| |
| − | | rs2 || 18 || 55940115 || 0.02 || EUR || blue
| |
| − | |-
| |
| − | | rs3 || 18 || 56000000 || 0.03 || AFR || green
| |
| − | |-
| |
| − | | rs4 || 18 || 56022000 || 0.03 || AFR || green
| |
| − | |-
| |
| − | | rs3 || 18 || 56100000 || 0.03 || ASN || purple
| |
| − | |-
| |
| − | | rs3 || 18 || 56150000 || 0.03 || ASN || purple
| |
| − | |-
| |
| − | | rs4 || 18 || 56160000 || 0.03 || ASN || purple
| |
| − | |-
| |
| − | | rs4 || 18 || 56180000 || 0.03 || ASN || purple
| |
| − | |-
| |
| − | |}
| |
| − | | |
| − | LocusZoom will extract from the file only those SNPs falling within the region to be plotted, so you can provide all of your fine-mapping results in a single file.
| |
| − | | |
| − | | |
| − | The generated plot will have a track showing the fine-mapping SNPs:
| |
| − | | |
| − | [[File:New lz finemap.png|900px]]
| |
| − | | |
| − | | |
| − | If the R package '''gridExtra''' is installed, the PDF will also have a summary of each fine-mapping SNP:
| |
| − | | |
| − | [[File:New lz finemap summary.png|400px]]
| |
| − | | |
| − | | |
| − | === Labeling multiple SNPs ===
| |
| − | | |
| − | You can specify a file controlling the labels for either the reference SNP, or any other arbitrary SNP within the region. For example:
| |
| − | | |
| − | [[File:New lz denote markers.png|700px]]
| |
| − | | |
| − | Use the --denote-markers-file <file> argument to do this:
| |
| − | | |
| − | <syntaxhighlight lang="bash">
| |
| − | locuszoom ... --denote-markers-file <your file>
| |
| − | </syntaxhighlight>
| |
| − | | |
| − | The file looks like:
| |
| − | | |
| − | {|
| |
| − | |-
| |
| − | ! scope="col" align="left" | snp
| |
| − | ! scope="col" align="left" | string
| |
| − | ! scope="col" align="left" | color
| |
| − | |-
| |
| − | | rs231362 || GWAS || blue
| |
| − | |-
| |
| − | | rs163184 || Conditional || purple
| |
| − | |-
| |
| − | |}
| |
| − | | |
| − | It must be tab-delimited and the columns must have a header and be named as such.
| |
| − | | |
| − | == Output ==
| |
| − | | |
| − | LocusZoom will produce a directory for each plot that contains the plot itself, along with a number of temporary files containing information on your particular region. The plot will be a PDF, named with the chr#:start-stop that was plotted.
| |
| − | | |
| − | If you only want the PDF itself, and don't want the other files, you can use the <code>--plotonly</code> option.
| |
| − | | |
| − | Each directory (or PDF, in the case of <code>--plotonly</code>) will have the date included to avoid collisions with previous plots - this behavior can be disabled using <code>--no-date</code>.
| |
| − | | |
| − | You can further customize the directory/PDF names that are created by using the <code>--prefix <name></code> option. This will append a text string at the beginning of each directory/PDF that is created.
| |
| − | | |
| − | == LocusZoom options ==
| |
| − | | |
| − | LocusZoom has a number of command line options, described in the table below.
| |
| − | | |
| − | {| width="85%" cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | Option
| |
| − | ! scope="col" | Description
| |
| − | |-
| |
| − | | colspan="2" | Important settings
| |
| − | |-
| |
| − | | --metal
| |
| − | | This is the data file to provide. Files generated by the meta-analysis program METAL are already formatted appropriately. If your data is not from METAL, it is very simple to format it (see [[#Input|Input]].)
| |
| − | |-
| |
| − | | --delim
| |
| − | | Delimiter for the data file. This defaults to tab, but can be anything. For ease of specification, you can use the following shortcuts: --delim tab, --delim space, --delim comma.
| |
| − | |-
| |
| − | | --pvalcol
| |
| − | | Name of p-value column in the --metal file.
| |
| − | |-
| |
| − | | --markercol
| |
| − | | Name of the SNP column in the --metal file.
| |
| − | |-
| |
| − | | --epacts
| |
| − | | Provide a results file generated by [[EPACTS]] instead of a --metal file.
| |
| − | |-
| |
| − | | --refsnp
| |
| − | | Reference SNP to be used in the plot.
| |
| − | |-
| |
| − | | --refgene
| |
| − | | Specify a gene instead of a reference SNP. This will plot a region near a gene, and automatically find the SNP with the most significant p-value to use as the reference SNP.
| |
| − | |-
| |
| − | | --flank
| |
| − | | Specify the region near a reference SNP or gene as a "flank", instead of having to specify chr/start/stop explicitly. This can be specified in bases, kilobases, or megabases. Examples: 500kb, 1MB, 100141
| |
| − | |-
| |
| − | | --chr, --start, --end
| |
| − | | Specify chromosome/start/stop as the exact interval to plot. If no --refsnp is specified, the SNP with the most significant p-value in the region will be used as the reference SNP.
| |
| − | |-
| |
| − | | colspan="2" | Optional settings
| |
| − | |-
| |
| − | | --build
| |
| − | | Human genome build. This defaults to "hg18", and is the only build we provide data for currently. You can supply your own build-specific data by modifying the conf file, and creating your own SQLite database (see *LINK HERE*).
| |
| − | |-
| |
| − | | --ld
| |
| − | | Provide a file specifying LD between your reference SNP and all SNPs within the region you wish to plot. You only need to supply this file if you have created LD specifically for your purposes (perhaps a different population or genome build.) Otherwise, LD is computed automatically for you.
| |
| − | |-
| |
| − | | --ld-vcf
| |
| − | | Use a VCF file to calculate LD between SNPs. This can be a VCF file with an entire genome of SNPs and does not have to be subsetted to your region. The VCF file must also have a tabix index file. For calculating D', the VCF must be phased.
| |
| − | |-
| |
| − | | --source
| |
| − | | Source to use for genotypes when using LD. See [[#Specifying_LD_source.2Fpopulation.2Fbuild|Specifying LD source/population/build]] for more info.
| |
| − | |-
| |
| − | | --pop
| |
| − | | Population to use when computing LD. See [[#Specifying_LD_source.2Fpopulation.2Fbuild|Specifying LD source/population/build]] for more info.
| |
| − | |-
| |
| − | | --snpset
| |
| − | | Rug of SNPs to create at the top of the plot. Defaults to the Illumina 1M chip currently. To disable, use --snpset NULL.
| |
| − | |-
| |
| − | | --plotonly
| |
| − | | Create only a PDF of the plot, and remove all temporary files/directories created during plotting.
| |
| − | |-
| |
| − | | --no-transform
| |
| − | | LocusZoom supports arbitrary precision p-values. However, if your p-values have already been transformed to the log scale, you can use this option to stop LocusZoom from automatically transforming them.
| |
| − | |-
| |
| − | | --prefix
| |
| − | | Places a text string at the beginning of each plot or directory created. This is mainly used to denote different batches of plots - for example, you could use --prefix using_ceu to denote these plots are computed using CEU LD information.
| |
| − | |-
| |
| − | | --db
| |
| − | | SQLite database file to use. This is set in the conf file by default, but can be changed on the command line if desired.
| |
| − | |}
| |
| − | | |
| − | <br>
| |
| − | | |
| − | <br>
| |
| − | | |
| − | == Plotting options ==
| |
| − | | |
| − | In addition to the options above, there are options that control the plotting engine inside Locuszoom. These are used with a different syntax: arg=value (no spaces allowed).
| |
| − | | |
| − | {| width="85%" cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | Option (with default value)
| |
| − | ! scope="col" | Description
| |
| − | |-
| |
| − | | theme=NULL
| |
| − | | Select a theme. A theme is a collection of other settings. Options include theme=publication and theme=black.
| |
| − | |-
| |
| − | | ymax=10
| |
| − | | the display range for log10(p-value) will be at least ymax (extended as necessary to avoid clipping)
| |
| − | |-
| |
| − | | axisSize=1
| |
| − | | scaling factor for axes
| |
| − | |-
| |
| − | | axisTextSize=1
| |
| − | | sclaing factor for axis labels
| |
| − | |-
| |
| − | | axisTextColor=gray30
| |
| − | | color of axis labels
| |
| − | |-
| |
| − | | refsnpTextColor=black
| |
| − | | color for reference SNP label (use 'transparent' to hide this label)
| |
| − | |-
| |
| − | | refsnpTextSize=1
| |
| − | | scaling factor for reference SNP text size
| |
| − | |-
| |
| − | | refsnpTextAlpha=1
| |
| − | | transparency level for reference SNP label (1=opaque,0=transparent)
| |
| − | |-
| |
| − | | title = ""
| |
| − | | title for plot
| |
| − | |-
| |
| − | | titleColor=black
| |
| − | | color for title
| |
| − | |-
| |
| − | | width=10
| |
| − | | width of pdf (inches)
| |
| − | |-
| |
| − | | height=7
| |
| − | | height of pdf (inches)
| |
| − | |-
| |
| − | | leftMarginLines=5
| |
| − | | margin (in lines) on left
| |
| − | |-
| |
| − | | rightMarginLines=5
| |
| − | | margin (in lines) on right
| |
| − | |-
| |
| − | | unit=1000000
| |
| − | | bp per unit displayed in plot
| |
| − | |-
| |
| − | | showAnnot=TRUE
| |
| − | | show annotation for each snp?
| |
| − | |-
| |
| − | | showGenes=TRUE
| |
| − | | show genes?
| |
| − | |-
| |
| − | | annotCol='annotation'
| |
| − | | column to use for custom annotation, if it exists
| |
| − | |-
| |
| − | | annotPch='24,24,25,22,22,8,7,21'
| |
| − | | plot symbols for annotation
| |
| − | |-
| |
| − | | annotOrder=NULL
| |
| − | | ordering of custom annotation classes (comma-separated list annotation strings in order, alphabetical by default)
| |
| − | |-
| |
| − | | showRefsnpAnnot=TRUE
| |
| − | | show annotation for reference snp too?
| |
| − | |-
| |
| − | | ld=NULL
| |
| − | | file for LD information
| |
| − | |-
| |
| − | | ldCuts="0,.2,.4,.6,.8,1"
| |
| − | | cut points for LD coloring
| |
| − | |-
| |
| − | | ldColors="gray50,navy, lightskyblue,green, orange,red,purple3"
| |
| − | | colors for LD
| |
| − | |-
| |
| − | | ldCol='rsquare'
| |
| − | | name for LD column
| |
| − | |-
| |
| − | | LDTitle=NULL
| |
| − | | title for LD legend
| |
| − | |-
| |
| − | | smallDot=.4
| |
| − | | smallest p-value cex
| |
| − | |-
| |
| − | | largeDot=.8
| |
| − | | largest p-value cex
| |
| − | |-
| |
| − | | refDot=NULL
| |
| − | | largest p-value cex
| |
| − | |-
| |
| − | | rfrows=4
| |
| − | | max number of rows used for displaying genes
| |
| − | |-
| |
| − | | showPartialGenes=TRUE
| |
| − | | should genes that don't fit completely be displayed?
| |
| − | |-
| |
| − | | geneFontSize=.8
| |
| − | | size for gene names
| |
| − | |-
| |
| − | | geneColor="navy"
| |
| − | | color for genes
| |
| − | |-
| |
| − | | snpsetFile=NULL
| |
| − | | use this file for SNPset rug data
| |
| − | |-
| |
| − | | rugColor=gray30
| |
| − | | color for snpset rugs
| |
| − | |-
| |
| − | | rugAlpha=1
| |
| − | | alpha for snpset rugs
| |
| − | |-
| |
| − | | metalRug=NULL
| |
| − | | if not null, use as label for rug of metal positions
| |
| − | |-
| |
| − | | showRecomb=TRUE
| |
| − | | show recombination rate?
| |
| − | |-
| |
| − | | recombColor=blue
| |
| − | | color for recombination rate on plot
| |
| − | |-
| |
| − | | recombAxisColor=NULL
| |
| − | | color for recombination rate axis labeing (default matches recombColor)
| |
| − | |-
| |
| − | | recombAxisAlpha=NULL
| |
| − | | color for recombination rate axis labeing
| |
| − | |-
| |
| − | | recombOver=FALSE
| |
| − | | overlay recombination rate? (else underlay it)
| |
| − | |-
| |
| − | | recombFill=FALSE
| |
| − | | fill recombination rate? (else line only)
| |
| − | |-
| |
| − | | recombFillAlpha=0.2
| |
| − | | recomb fill alpha
| |
| − | |-
| |
| − | | recombLineAlpha=0.8
| |
| − | | recomb line/text alpha
| |
| − | |-
| |
| − | | frameColor=gray30
| |
| − | | frame color for plots
| |
| − | |-
| |
| − | | frameAlpha=1
| |
| − | | frame alpha for plots
| |
| − | |-
| |
| − | | legendSize=.8
| |
| − | | scaling factor of legend
| |
| − | |-
| |
| − | | legendAlpha=1
| |
| − | | transparency of legend background
| |
| − | |-
| |
| − | | legend='auto'
| |
| − | | legend? (auto, left, right, or none)
| |
| − | |-
| |
| − | | hiStart=0
| |
| − | | start of highlighted region
| |
| − | |-
| |
| − | | hiEnd=0
| |
| − | | end of highlighted region
| |
| − | |-
| |
| − | | hiColor=blue
| |
| − | | color used for highlighting
| |
| − | |-
| |
| − | | hiAlpha=0.1
| |
| − | | transparency level for highlighting
| |
| − | |-
| |
| − | | prelude=NULL
| |
| − | | R code to execute after data is read but before plot is made (allows data modification)
| |
| − | |-
| |
| − | | postlude=NULL,
| |
| − | | R code to execute after plot is made
| |
| − | |}
| |
| − | | |
| − | <br>
| |
| − | | |
| − | <br>
| |
| − | | |
| − | == Examples ==
| |
| − | | |
| − | === A quick peek at a particular SNP ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs1002227
| |
| − | </pre>
| |
| − | === A quick peek at a particular gene ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refgene CETP
| |
| − | </pre>
| |
| − | === Plot 500kb on either side of a SNP ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs7983146 --flank 500kb
| |
| − | </pre>
| |
| − | === Use 1000 genomes, CEU for LD instead of the default (HapMap r22 CEU) ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs11899863 --source 1000G
| |
| − | </pre>
| |
| − | | |
| − | === Use HapMap YRI for LD ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs11899863 --pop YRI --build hg18 --source hapmap
| |
| − | </pre>
| |
| − | | |
| − | === Specify a specific region and reference SNP to plot ===
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs1552224 --chr 11 --start 71810746 --end 72710746
| |
| − | </pre>
| |
| − | | |
| − | === An example using plotting options ===
| |
| − | | |
| − | Note in this example the plotting options are placed at the '''end''' of the command-line, and are of the format '''arg'''='''value'''. The value should be double-quoted if spaces are included in the value (see title= below.)
| |
| − | | |
| − | <code></code>
| |
| − | <pre>--metal your_data --refsnp rs7903146 title="My region" geneFontSize=1.1 recombColor="gray"
| |
| − | </pre>
| |
| − | | |
| − | == Advanced configuration ==
| |
| − | | |
| − | === Creating a SQLite database ===
| |
| − | | |
| − | As a starting point, we provide a SQLite database based on UCSC human genome '''build hg18''', which includes the following tables:
| |
| − | | |
| − | *snp_pos: SNP positions
| |
| − | *refFlat: gene information (exons, transcription start/stops, etc.)
| |
| − | *recomb_rate: recombination rates from hapmap phase 2
| |
| − | *snp_set: maps each SNP to a "set" - for example, all SNPs on the Illumina 1M chip
| |
| − | *refsnp_trans: a table that maps SNPs from previous builds to the current build
| |
| − | | |
| − | To create your own database, we provide a script <code>bin/dbmeister.py</code> that can insert these tables for you. We recommend creating your own database file, rather than inserting tables into the default LocusZoom database. This script is capable of using python's built-in sqlite support, but for faster insertion of tables (about 2x faster), we recommend installing sqlite3 from [http://www.sqlite.org/ www.sqlite.org].
| |
| − | | |
| − | ==== Inserting snp_pos ====
| |
| − | | |
| − | First, create a file that looks like the following:
| |
| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1" class="sortable"
| |
| − | |-
| |
| − | ! scope="col" | snp
| |
| − | ! scope="col" | chr
| |
| − | ! scope="col" | pos
| |
| − | |-
| |
| − | | rs38343
| |
| − | | 1
| |
| − | | 93919141
| |
| − | |-
| |
| − | | rs918141
| |
| − | | 7
| |
| − | | 763263
| |
| − | |-
| |
| − | | chr4:9181
| |
| − | | 4
| |
| − | | 9181
| |
| − | |}
| |
| − | | |
| − | The file should be: tab-delimited, must have a header, and the columns should be exactly in that order.
| |
| − | | |
| − | Now, you can create your own database, and insert this file by using:
| |
| − | <pre> dbmeister.py --db my_database.db --snp_pos my_snp_pos_file </pre>
| |
| − | This command creates a database called "my_database.db" and inserts the SNP position table into it. If "my_database.db" had existed already, it would drop the snp_pos table in it, and insert yours in its place.
| |
| − | | |
| − | One special note about adding SNP position tables: a refsnp_trans table will automatically be created for you, where each SNP maps to itself. If you have a list of SNPs from previous builds that you would like to map to a SNP in the current build, you can then insert your own refsnp_trans table (see below for more information on this table.)
| |
| − | | |
| − | ==== Inserting refsnp_trans ====
| |
| − | | |
| − | The refsnp_trans table looks like the following:
| |
| − | | |
| − | {| width="75%" cellspacing="0" cellpadding="5" border="1" class="sortable"
| |
| − | |-
| |
| − | ! scope="col" | rs_orig
| |
| − | ! scope="col" | rs_current
| |
| − | |-
| |
| − | | rs840
| |
| − | | rs715
| |
| − | |-
| |
| − | | rs1086
| |
| − | | rs940
| |
| − | |-
| |
| − | | rs1234
| |
| − | | rs1067
| |
| − | |}
| |
| − | | |
| − | The first column contains SNP names from older genome builds, and the rs_current column contains SNP names from the current genome build (i.e., the build your database file is anchored to.)
| |
| − | | |
| − | Inserting this table into your database is simply then:
| |
| − | <pre> dbmeister.py --db my_database.db --trans my_snp_translations_file </pre>
| |
| − | You will want to execute this command AFTER inserting the snp_pos table, since that command drops the existing translation table.
| |
| − | | |
| − | ==== Inserting refFlat ====
| |
| − | | |
| − | The refFlat table mirrors what is currently supplied by the refFlat table in the UCSC database. The file should look like:
| |
| − | | |
| − | {| cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | geneName
| |
| − | ! scope="col" | name
| |
| − | ! scope="col" | chrom
| |
| − | ! scope="col" | strand
| |
| − | ! scope="col" | txStart
| |
| − | ! scope="col" | txEnd
| |
| − | ! scope="col" | cdsStart
| |
| − | ! scope="col" | cdsEnd
| |
| − | ! scope="col" | exonCount
| |
| − | ! scope="col" | exonStarts
| |
| − | ! scope="col" | exonEnds
| |
| − | |-
| |
| − | | EFCAB1
| |
| − | | NM_024593
| |
| − | | chr8
| |
| − | | -
| |
| − | | 49798505
| |
| − | | 49810423
| |
| − | | 49799853
| |
| − | | 49810263
| |
| − | | 6
| |
| − | | 49798505,
| |
| − | | 49799913,
| |
| − | |-
| |
| − | | HECTD3
| |
| − | | NM_024602
| |
| − | | chr1
| |
| − | | -
| |
| − | | 45240806
| |
| − | | 45249614
| |
| − | | 45241750
| |
| − | | 45249516
| |
| − | | 21
| |
| − | | 45240806,45241927,
| |
| − | | 45241835,45241999,
| |
| − | |-
| |
| − | | PTPN20B
| |
| − | | NM_001042361
| |
| − | | chr10
| |
| − | | -
| |
| − | | 48357047
| |
| − | | 48447587
| |
| − | | 48358657
| |
| − | | 48447532
| |
| − | | 8
| |
| − | | 48357047,48359393,48391320,
| |
| − | | 48358692,48359456,48391411,
| |
| − | |}
| |
| − | | |
| − | You can insert this table into the database using:
| |
| − | <pre> dbmeister.py --db my_database.db --refflat my_refflat_file </pre>
| |
| − | ==== Inserting recomb_rate ====
| |
| − | | |
| − | The recomb_rate table mirrors what is available from [ftp://ftp.hapmap.org/hapmap/recombination/2008-03_rel22_B36/rates/ HapMap]. The format is:
| |
| − | | |
| − | {| cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | chr
| |
| − | ! scope="col" | pos
| |
| − | ! scope="col" | recomb
| |
| − | ! scope="col" | cm_pos
| |
| − | |-
| |
| − | | 1
| |
| − | | 72434
| |
| − | | 0.0015
| |
| − | | 0
| |
| − | |-
| |
| − | | 1
| |
| − | | 78032
| |
| − | | 0.0015
| |
| − | | 8.397e-06
| |
| − | |-
| |
| − | | 1
| |
| − | | 554461
| |
| − | | 0.0015
| |
| − | | 0.00072304
| |
| − | |-
| |
| − | | 1
| |
| − | | 554484
| |
| − | | 0.0015
| |
| − | | 0.000723075
| |
| − | |-
| |
| − | | 1
| |
| − | | 555296
| |
| − | | 0.0015
| |
| − | | 0.000724293
| |
| − | |-
| |
| − | | 1
| |
| − | | 558185
| |
| − | | 0.0015
| |
| − | | 0.000728627
| |
| − | |}
| |
| − | | |
| − | The table can be inserted using:
| |
| − | <pre> dbmeister.py --db my_database.db --recomb_rate my_recomb_rate_file </pre>
| |
| − | ==== Inserting snp_set ====
| |
| − | | |
| − | The snp_set table simply carries a mapping of SNPs to a particular set they may belong to. The table looks like:
| |
| − | | |
| − | {| cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | snp
| |
| − | ! scope="col" | snp_set
| |
| − | |-
| |
| − | | rs1000
| |
| − | | Illu1M
| |
| − | |-
| |
| − | | rs1000
| |
| − | | Illu1M
| |
| − | |-
| |
| − | | rs1000
| |
| − | | Illu1M
| |
| − | |-
| |
| − | | rs1000000
| |
| − | | Illu1M
| |
| − | |-
| |
| − | | rs10000000
| |
| − | | Illu1M
| |
| − | |-
| |
| − | | rs10000009
| |
| − | | Illu1M
| |
| − | |}
| |
| − | | |
| − | The first column is a SNP, and the second is the name of the set it belongs to. If a SNP belongs to multiple sets, you can duplicate that SNP multiple times, one for each set.
| |
| − | | |
| − | Inserting the table into your database can be done using:
| |
| − | <pre> dbmeister.py --db my_database.db --snp_set my_snpset_file </pre>
| |
| − | ==== Making LocusZoom aware of your new database ====
| |
| − | | |
| − | Now that you've created your own database file, you need to make LocusZoom aware that it exists. There are two ways to do this:
| |
| − | | |
| − | #Edit conf/m2zfast.conf, and change the <code>SQLITE_DB</code> variable
| |
| − | #Supply the <code>--db</code> command line option when invoking <code>bin/locuszoom</code>
| |
| − | | |
| − | Editing the m2zfast.conf file entails changing the following block of code:
| |
| − | | |
| − | <code></code>
| |
| − | <pre>SQLITE_DB = {
| |
| − | 'hg18' : "data/database/locuszoom_hg18.db"
| |
| − | };
| |
| − | </pre>
| |
| − | Here, we've mapped build "hg18" to the default database file that comes with LocusZoom. You can mimic this format and insert your own, for example:
| |
| − | | |
| − | <code></code>
| |
| − | <pre>SQLITE_DB = {
| |
| − | 'hg18' : "data/database/locuszoom_hg18.db",
| |
| − | 'hg19' : "data/database/my_database.db"
| |
| − | };
| |
| − | </pre>
| |
| − | The location of your database should be either an absolute path to your file, or a path relative to the locuszoom/ root (like those seen above.)
| |
| − | | |
| − | If you wish for your database to become the default, change the <code>LATEST_BUILD</code> variable in the m2zfast.conf file to whatever you have chosen above (in our example, our new database became mapped to 'hg19'.)
| |
| − | | |
| − | === Changing m2zfast.conf settings ===
| |
| − | | |
| − | The m2zfast.conf configuration file contains a number of settings that are typically static, but could require user configuration. The table below lists each variable, and its purpose.
| |
| − | | |
| − | {| cellspacing="0" cellpadding="5" border="1"
| |
| − | |-
| |
| − | ! scope="col" | Variable
| |
| − | ! scope="col" | Description
| |
| − | |-
| |
| − | | DEFAULT_BUILD
| |
| − | | Default build to use for finding SNP positions, and calculating LD. This is used to index SQLITE_DB, as well as LD_DB.
| |
| − | |-
| |
| − | | DEFAULT_POP
| |
| − | | Default population to use for computing LD.
| |
| − | |-
| |
| − | | DEFAULT_SOURCE
| |
| − | | Default source for computing LD.
| |
| − | |-
| |
| − | | NEWFUGUE_PATH
| |
| − | | Path to the new_fugue binary. Defaults to "new_fugue", which simply means it is searched for on your path. If new_fugue is not on your path, you will need to specify the full path here.
| |
| − | |-
| |
| − | | PLINK_PATH
| |
| − | | Path to the PLINK binary. Defaults to "plink", which searches for PLINK on your path. If it is not on your path, specify the full path here.
| |
| − | |-
| |
| − | | RSCRIPT_PATH
| |
| − | | Path to the Rscript binary. Defaults to "Rscript", which searches for Rscript on your path. If it is not on your path, specify the full path here.
| |
| − | |-
| |
| − | | SQLITE_DB
| |
| − | | See [[LocusZoom Standalone#Making_LocusZoom_aware_of_your_new_database|Making LocusZoom aware of your database]].
| |
| − | |-
| |
| − | | LD_DB
| |
| − | | Contains a "tree" which maps a tuple of (genotype source, genotype population, genome build) to genotype files.
| |
| − | |-
| |
| − | | GWAS_CATS
| |
| − | | Contains a "tree" which maps genome build and the name of a GWAS catalog to the actual file containing the GWAS hits.
| |
| − | |}
| |
| − | | |
| − | === LD caching ===
| |
| − | | |
| − | LocusZoom attempts to remember LD calculations that were made on previous runs of the program to avoid having to re-calculate the same regional LD for subsequent runs. The process works as follows:
| |
| − | | |
| − | *For a given reference SNP and chr/start/stop:
| |
| − | **If LD has not been previously computed, use new_fugue to compute LD with the reference SNP and all other SNPs in the region, and store this result to the LD cache
| |
| − | **Else, retrieve the previously stored LD results
| |
| − | | |
| − | The cache intelligently stores LD from separate sources (hapmap, 1000G), populations, builds, and even different versions of genotype files separately.
| |
| − | | |
| − | Upon running LocusZoom, a file called "ld_cache.db" will automatically be created in the current directory, and LD computations will be stored there. If you wish to change the location of the LD cache, use <code>--cache <file></code>. If you wish to disable LD caching, you can use <code>--cache None</code>.
| |
| − | | |
| − | ''Python note:'' The ld_cache.db is actually a shelve, and you can explore its contents using:
| |
| − | | |
| − | <code></code>
| |
| − | <pre>import shelve
| |
| − | d = shelve.open("ld_cache.db")
| |
| − | </pre>
| |
| − | == License ==
| |
| − | | |
| − | Copyright 2010 Ryan Welch, Randall Pruim
| |
| − | | |
| − | This program is free software: you can redistribute it and/or modify
| |
| − | it under the terms of the GNU General Public License as published by
| |
| − | the Free Software Foundation, either version 3 of the License, or
| |
| − | (at your option) any later version.
| |
| − | | |
| − | This program is distributed in the hope that it will be useful,
| |
| − | but WITHOUT ANY WARRANTY; without even the implied warranty of
| |
| − | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
| |
| − | GNU General Public License for more details.
| |
| − | | |
| − | [[Category:Software]] | |
