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cgrace1978 Changed properties of the max.count variable in the config file.
max.count now is the top value that a bin can take, rather than the top value + 1.
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MANHATTAN++ is software to generate a transposed manhattan heatmap, implemented in R.

Getting Started

You need to install the latest version of R The R package can be run on Windows and Linux, you must specify paths to the filenames you are using as input and output.

To install the software from the GIT repository:


install_github("cgrace1978/manhplot", dependencies = T, force = T)

Note: If you are using the default GWAS file (cad.add.160614_manhformat.txt.gz) it must be unzipped prior to running the R script.

The following command will run the plot with default data in the package:

## install R.utils in order to unzip the GWAS file.


## unzip the GWAS file
gunzip(system.file("extdata","cad.add.160614_manhformat.txt.gz",package = "manhplot"))

infile<-system.file("extdata","cad.add.160614_manhformat.txt",package = "manhplot")
configfile<-system.file("extdata","config.txt", package = "manhplot")
snpfile<-system.file("extdata","56cad.add.160614.variants.txt", package = "manhplot")

## Run manhattan++ with the default paramaters and files included in the package
manhplusplot(infile = infile,outfile = "test", configfile = configfile, snpfile = snpfile)

## zip the GWAS file
gzip(system.file("extdata","cad.add.160614_manhformat.txt",package = "manhplot"))

Input Files

In order to generate the plot, three files are required (with headers in the format described)

Genome Wide Association Study (GWAS) or Meta-analysis summary statistics

The summary statistics, this file should have the following columns:

  1. chr - chromosome (must be numeric)
  2. pos - position
  3. pvalue - p-value (please do not log-transform)
  4. maf - Minor Allele Frequency
  5. conseq - Flag of whether variant has HIGH functional consequence (using VEP)

The variable infile should be modfied to point to this file (with the file structure of the operating system used). The files should be numerically sorted (chr:pos).

chr pos     pvalue      maf       conseq
1   751756  0.4528019   0.158264  0
1   752566  0.7394597   0.763018  0
1   752721  0.8462652   0.740969  0
1   752894  0.7750657   0.744287  0

HINT: The software's default is to displays MAF data when a MAF <5%. If you don't want to use this display function set the MAF function argument to 0.

HINT: The software displays annotation data when a consequence is 1. If you don't want to use this display function, give all SNPs a consequence of 0

HINT: You can use different column names for the GWAS files by using the command line arguments:

## Use different GWAS file column names using: chrname, posname, pvalname, frqname and conseqname
manhplot(infile = infile,outfile = "test", configfile = configfile, snpfile = snpfile,
         chrname = "chr", posname = "pos", pvalname = "pvalue", frqname = "maf",
         conseqname = "conseq",)

Loci information (variants)

Variants of interest to annotate the plot with.

  1. markername - The name of the variant
  2. NearestGene - The gene name associated with the variant
  3. chr - chromosome
  4. pos - position
  5. eaf - effect allele frequency
  6. OR - Odds Ratio
  7. Pvalue - P-value
  8. novel - Flag for whether the variant is novel (a new loci)

The variable snpfile should be modfied to point to this file (with the file structure of the operating system used). The novel flag indicates whether the loci is a new finding in the GWAS being reported. When the showGenes flag is set to TRUE, Novel loci will be displayed in the table and the others on the heatmap, as bubble labels. When showGenes is false, all loci are displayed in the table.

markername  NearestGene chr     pos         eaf       OR      Pvalue    novel
rs11206510  PCSK9       1       55496039    0.847627  1.08    2.34E-08  FALSE
rs9970807   PPAP2B      1       56965664    0.915097  1.13    5E-14     FALSE
rs7528419   SORT1       1       109817192   0.78582   1.12    1.97E-23  FALSE

Configuration file

To define the legend and type of heatmap cells.

  1. min.count - Lower bounds of number of variants in this cell
  2. max.count - Upper bounds of number of variants in this cell.
  3. maf - Should variants with minor allele frequencies below the threshold be detected by this cell?
  4. conseq - Should any HIGH consequence variant be detected?
  5. col - The colour of the heatmap cells
  6. idx - Index for labeling on the heatmap
  7. type - The type of cell: val or oddchr / evenchr
  8. report - Should these cells be reported on the heatmap with bubble label?

The variable configfile should be modfied to point to this file (with the file structure of the operating system used)

#### CONFIG file for use with MANH++ - Do not modify the first 10 lines							
## min.count: The lower cell count threshold to accept this config							
## max.count: The upper cell count threshold to accept this config							
## maf: Is MAF detection active for this config - is there any variants within a cell with MAF < threshold?	
## conseq: Is HIGH impact consequence active? Are there any variants with HIGH impact consequence in the cell?		
## col: The colour which cells for this config							
## idx: the index to use for this cell in the heatmap - MUST BE CONSECUTIVE FROM START TO END - STARTING AT 1
## type: val - an config entry, oddchr - the odd chromosome, evenchr - the even chromosome"		
## report: Are these annotations labeled on the heatmap							
min.count   max.count   maf     conseq    col         idx     type    report
1           2           FALSE   FALSE     black       1       val     FALSE
1           2           FALSE   TRUE      light pink  2       val     TRUE
1           2           TRUE    FALSE     green       3       val     FALSE

Also see the example file (config.txt) for more information.

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