python tobed.py Regression_SEX_AGE_LNIGE_DDAST_AgeSex_oriPred_FDR.csv | sort -k1,1 -k2,2n > pvalues.bed
set -e

c=4
for p in pAge pSex pAgeSex pLNIGE pDDAST; do
    PREFIX=data/$p
    awk '($'$c'!= "NA")' pvalues.bed > t.bed

    python ~/src/combined-pvalues/cpv/comb-p.py pipeline \
        -c $c --dist 160 --step 40 \
        --seed 0.05 -p $PREFIX \
        t.bed
    # print chrom,start,end,n-probes,slk-sidak-p
    awk '($7 < 0.1){ print $1,$2,$3,$5,$7 }' $PREFIX.regions-p.bed > $PREFIX.filter.bed

    python ~/src/bio-playground/superbed/superanno.py \
        -a $PREFIX.filter.bed \
        -b ~/src/denver-bio/lgrc-charm/data/hg18.super.bed \
        --header > $PREFIX.cpv.txt

    python ~/src/combined-pvalues/cpv/manhattan.py --image \
            $PREFIX.manhattan.png --ymax 12 --col 5 $PREFIX.fdr.bed

    c=$(($c + 1))
done