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# Meta analyse pipeline: `assoc/main.nf`

MetaAnalysis pipeline : assoc/meta-assoc.nf

This section describes a pipeline in devlopment, purpose of this pipeline is to do a meta analysis with a various format files.Our script, meta-assoc.nf takes as input various GWAS results files and rsid to do a metanalysis with METAL, GWAMA and Metasoft

Installation

need python3, METAL (last version : https://github.com/statgen/METAL), GWAMA, MR-MEGA and MetaSoft (one version is available on utils/bin/)

Option

The key options are:

  • work_dir : the directory in which you will run the workflow. This will typically be the h3agwas directory which you cloned;
  • input, output and script directories: the default is that these are subdirectories of the work_dir and there'll seldom be reason to change these;
  • output_dir = "all"
  • meta analysis option :
    • metal : 1 perform metal (default 0)
    • gwama : 1 perform gwama (default 0)
    • plink : 1 perform perform meta analyse in plink(default 0)
    • metasoft : 1 perform metasoft(default 0)
      • metasoft_pvalue_table : for metasoft need files : HanEskinPvalueTable.txt
    • mrmega : 1 perform MR-MEGA (default 0)
  • file_config
    • describe all informations for each gwas result used for meta analysis
    • file is comma separated (csv), each line is to describe one file
    • header of config file is : rsID,Chro,Pos,A1,A2,Beta,Se,Pval,N,freqA1,direction,Imputed,Sep,File,IsRefFile
      • rsID : column name for rsID in gwas file
      • Chro : column name for Chro in gwas file
      • Pos : column name for Pos in gwas file
      • A1 : column name for reference allele in gwas file
      • A2 : column name for alternative allele in gwas file
      • Beta : column name for B values in gwas file
      • Se : column name for sterr values in gwas file
      • N : column name for size in gwas file
      • freqA1 : column name for freqA1 or maf in gwas file
      • direction : column name of strand for association -/+ in gwas file
      • Imputed : column name of imputed or not for position in gwas file
      • NCount : column name to add a column N at your file with value in the column
      • Sep : what separator is in gwas file :
        • you could use characters as ; . : but to avoid some trouble you can use :
          • COM : for comma
          • TAB : for tabulation
          • WHI : for white space
      • File : gwas file with full path
      • if one of the column is missing in your GWAS file, replace by NA
  • optional option :
    • memorie usage :
      • plink_mem_req : [20GB]
      • gwama_mem_req : gwama memories [20GB]
      • metasoft_mem_req : metasoft memories ["20G"]
      • ma_mem_req : request for extraction of data, change format and plot of manhathan ["10G"]
      • mrmega_mem_req : mr mega memorie ["20GB"]
    • used_pval_z : computed beta and se usinf pvalue and sign of initial beta, n value and frequency [defaul 0:no]
    • formula to computed beta and se
    z=abs(stats.norm.ppf(1-pinit/2))*sens
    b=z/sqrt(2*freq*(1-freq)*(n+z**2))
    se=1/sqrt(2*freq*(1-freq)*(n+z**2))

 * cpu and memories :
    * max_plink_cores : [default 4]
    * other used 1 cpus
 * binaries :
   * `metal_bin` : binarie for metal (default : _metal_ )
   * `gwama_bin` :  binarie for gwama ( default : _GWAMA__ )
   * `metasoft_bin` : binarie for java of metasoft ( default _Metasoft.jar_)
   * `mrmega_bin` : binarie for java of metasoft ( default _Metasoft.jar_)
   * `plink_bin` : binarie for java of metasoft ( default _Metasoft.jar_)
 * options software :
   * `ma_metasoft_opt` : append other option in metasoft command line(default : null)
   * `ma_genomic_cont` : use a genomic_control use in METAL and GWAMA(default, 0)
   * `ma_weigthedz`: used p-value and N params for plink and metal (default: 0), if 1 used pvalue and N otherwise used Beta and se
   * `ma_overlap_sample`: do you have sample overlap? used by metal(default: 0)
   * `metal_het`: computed heterogenity option used by metal (default: 0)
   * `ma_random_effect` : do mixed model (default 1)
   * `ma_mrmega_pc` : how many pcs used for mrmega (default : 4)
   * `ma_mrmega_opt` : append other option in MR-MEGA command line (default : null)
* `us_rs` : if you want chromosome and position are replaced using rs (warning you need to be sure that one chromosome position has same rs in each file), [default 0, yes : 1], otherwise they will used chromosome and position to replaced rs

specificity

MR-MEGA

MR-MEGA need chromosomes, positions and N (sample number) for each position, so in pipeline referent file (in file_config, 1 in IsRefFile) must be have chromosome and poosition

option comparaison software

| | options |

Software ma_genomic_cont ma_weigthedz ma_overlap_sample ma_random_effect
descriptionus genomic control used p-value and N (1) or beta and se (0) sample overlap Random Effect
default 0 0 0 0
metal yes yes yes no
gwama yes default no yes
Mr Mega yes no no no
plink no yes no no
Metasoft no no no default
--- --- --- --- ---

1 ma_weigthedz requests weighted Z-score-based p-values (as computed by the Abecasis Lab's METAL software)

Ressource

Software Manuals References
Metal here here
Gwama here here
Mr Mega here here
plink here here
Metasoft here here
--- --- ---

References

Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

Example

  • data and command line can be found h3agwas-examples
  • a csv file need to described each input, contains header for each file
echo "rsID,Chro,Pos,A1,A2,Beta,Se,Pval,N,freqA1,direction,Imputed,Sep,File,Ncount" > utils/input_meta.csv
for File in `ls data/summarystat/*.gemma|grep -v ".all"`
do
echo "rs,chr,ps,allele0,allele1,beta,se,p_wald,NA,af,NA,NA,TAB,$File,2500" >>  utils/input_meta.csv
done
  • input :
    • user can choose software that he want to run : metal (--metal 1), gwama (--gwama 1), metasoft ( --metasoft 1) MrMega (--mrmega 1) and plink (--plink 1)
nextflow run ~/Travail/git/h3agwas/meta/meta-assoc.nf   --metal 1 --gwama 1 --metasoft 1 --mrmega 1 --plink  1  --file_config utils/input_meta.csv -resume -profile slurmSingularity --output_dir meta

Mtag analysis

reference

parameters

  • file_gwas : one ore more one file gwas of differents phenotype
    • ̀head_pval` : pvalue header [ default : "P_BOLT_LMM" ]
    • head_n : N (individuals number) [ default : None ], if not present computed with plink (and data/pheno if present)
    • head_rs : rs header column [default : "SNP"]
    • head_beta : beta header colum [default : "BETA"]
    • head_se : column for standard error of beta "SE"
    • head_A1 : column for A0 :[default : "ALLELE0" ]
    • head_A2 : column for A0 :[default : "ALLELE2" ]
    • head_freq : freq header [ default : A1Freq],
    • head_n: N header, used just for ldsc, if not present, Nind must be initialize.
  • if n not initialise :
    • used plink file to computed each position with n :
    • input_pat : input pattern of plink file
    • input_dir : input dir of plink file
    • list_n : need to be implemented

Example

  • data and command line can be found h3agwas-examples
  • multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples.
  • input :
  • list of summary statistic file_gwas and header from gwas file: -head_[name]
  • also you can give nformation relative to : --input_dir data/imputed/ --input_pat imput_data --pheno pheno_qt1,pheno_qt2 --data data/pheno/pheno_test.all, can add N value to each summary statistic
nextflow h3abionet/h3agwas/meta/mtag-assoc.nf --head_freq af --head_pval p_wald --head_bp ps --head_chr chr --head_rs rs --head_beta beta --head_se se --head_A1 allele1 --head_A2 allele0 --input_dir data/imputed/ --input_pat imput_data --file_gwas  data/summarystat/all_pheno.gemma,data/summarystat/all_phenoq2.gemma --pheno pheno_qt1,pheno_qt2 --data data/pheno/pheno_test.all -resume   -profile slurmSingularity