dev/gwas/DownloadDbGap2.r

In zhezhangsh/rchive:

################################################################################
# Download and process GWAS results from dbGap
DownloadDbGap2<-function(url="ftp://ftp.ncbi.nlm.nih.gov/dbgap//Analysis_Table_of_Contents.txt", 
                        path=paste(Sys.getenv("RCHIVE_HOME"), 'data/gwas/public/dbgap', sep='/'), 
                        update.all.analysis=FALSE,
                        redundant.studies=c('216', '88', '342')) {
  # url                   File with analysis metadata and download location
  # path                  Path to output files
  # update.all.analysis   Re-download all PubMed entries if TRUE, takes very long time to do so
  # redundant.studies     Exclude redundant studies of the same analyses belong to other studys
  
  library(RCurl);
  library(rchive);
  
  if (!file.exists(path)) dir.create(path, recursive=TRUE);
  if (!file.exists(paste(path, 'r', sep='/'))) dir.create(paste(path, 'r', sep='/'), recursive=TRUE);
  if (!file.exists(paste(path, 'r/full_table', sep='/'))) dir.create(paste(path, 'r/full_table', sep='/'), recursive=TRUE);
  if (!file.exists(paste(path, 'src', sep='/'))) dir.create(paste(path, 'src', sep='/'), recursive=TRUE);
  
  # Original metadata with each ftp file of analysis; parsed into a table
  fn.meta<-paste(path, 'r', 'original_metadata.rds', sep='/');
  if (file.exists(fn.meta)) meta<-readRDS(fn.meta) else {
    emp<-character(0);
    meta<-data.frame(name=emp, study=emp, genome=emp, dbsnp=emp, description=emp, method=emp, file=emp, stringsAsFactors=FALSE);
    #saveRDS(meta, file=fn.meta);
  }
  # Original metadata with each ftp file of analysis; as a list
  fn.meta.lst<-paste(path, 'r', 'original_metadata_list.rds', sep='/');
  if (file.exists(fn.meta.lst)) meta.lst<-readRDS(fn.meta.lst) else {
    meta.lst<-list();
    #saveRDS(meta.lst, file=fn.meta.lst);
  }
  
  # Download and parse metadata table
  ln<-strsplit(getURL(url), '\n')[[1]];
  gw<-do.call('rbind', strsplit(ln, '\t'));
  colnames(gw)<-gw[1,];
  gw<-gw[-1, , drop=FALSE];
  gw<-data.frame(gw, stringsAsFactors=FALSE);
  gw<-gw[!(gw[,1] %in% redundant.studies), ];
  
  ######################################################################################
  # Download results of individual analyses
  # file information
  fn.ftp<-gw$analysis.result;
  fn.gz<-sapply(strsplit(fn.ftp, '/'), function(x) x[length(x)]);
  id.study<-sapply(strsplit(fn.gz, '\\.'), function(x) x[1]);
  id.analysis<-sapply(strsplit(fn.gz, '\\.'), function(x) x[2]);
  fn.gz<-paste(path, 'src', fn.gz, sep='/');
  fn.r<-paste(path, 'r/full_table', paste(id.analysis, '.rds', sep=''), sep='/');
  file.info<-cbind(analysis=id.analysis, study=id.study, ftp=fn.ftp, gz=fn.gz, r=fn.r);
  
  ####################################################################################
  # load in table and save to local
  loaded<-sub('.rds', '', sapply(strsplit(fn.r, '/'), function(x) x[length(x)]))
  no.meta<-!(loaded %in% rownames(meta)) | !(loaded %in% names(meta.lst)); # missing metadata info.
  if (update.all.analysis) no.tbl<-file.info else no.tbl<-file.info[!file.exists(file.info[, 'r']) | no.meta, , drop=FALSE];
  if (nrow(no.tbl) > 0) {
    hd<-lapply(1:nrow(no.tbl), function(i) {
      x<-no.tbl[i,];
      cat("loading analysis", x[1], '\n');
      if (!file.exists(x[4])) download.file(x[3], x[4]); 
      ln<-scan(x[4], what='', flush=TRUE, sep='\n');
      
      # very tediously parse file header and add header info to metadata table and list
      hd<-ln[substr(ln, 1, 2)=='# '];
      hd<-sub('^# ', '', hd);
      hd<-strsplit(hd, ':\t');
      hd<-lapply(hd, function(hd) sub('^ ', '', hd));
      hd<-lapply(hd, function(hd) sub(' $', '', hd));      
      hd<-do.call('rbind', hd);
      hd.nm<-tolower(hd[,1]);
      hd<-hd[,2];
      names(hd)<-hd.nm;
      
      # save full result table
      cnm<-strsplit(ln[length(hd)+1], '\t')[[1]];
      tbl<-strsplit(ln[(length(hd)+2):length(ln)], '\t');
      tbl<-t(sapply(tbl, function(x) x[1:length(cnm)]));
      tbl<-data.frame(tbl, stringsAsFactors=FALSE); # all columns are character
      colnames(tbl)<-cnm;
      saveRDS(tbl, x[5]);
      
      hd;
    })
    
    meta.lst[no.tbl[,1]]<-hd;
    new.rows<-sapply(1:length(hd), function(i) {
      hd<-hd[[i]];
      as.vector(c(hd['name'], no.tbl[i, 2], hd[c('human genome build', 'dbsnp build', 'description', 'method')], no.tbl[i, 3]));
    });
    new.rows<-t(new.rows);
    rownames(new.rows)<-no.tbl[,1];
    new.rows<-new.rows[!(rownames(new.rows) %in% rownames(meta)), , drop=FALSE];
    if (nrow(new.rows) > 0) {
      df<-data.frame(new.rows, stringsAsFactors=FALSE);
      colnames(df)<-colnames(meta);
      meta<-rbind(meta, df);
    }
  } 
  ####################################################################################
  
  saveRDS(meta[order(rownames(meta)), ], file=fn.meta);
  saveRDS(meta.lst[order(names(meta.lst))], file=fn.meta.lst);
  
  meta;
}