reczko@max:/data/images/proton/run342/www$ awk -f /data/images/proton/make-stranded-sampled-hg19-tracks1.awk reads-hsa.txt > make-stranded-sampled-hg19-tracks.sh
awk -f /data/images/proton/make-stranded-sampled-mm10-tracks1.awk  reads.txt  > make-stranded-sampled-mm10-tracks.sh
source make-stranded-sampled-mm10-tracks.sh


library(metaseqR)
the.path <- "/data/images/proton2/run342/www"
the.contrasts.1 <- c(
	"Grp4aMinus_vs_Grp4aPlus",
	"Grp4fMinus_vs_Grp4fPlus"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt"),
    contrast=the.contrasts.1,
    annotation="download",
    org="mm10",
    refdb="ensembl",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_quantseq_run342a"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias",
        "biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","mm10")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)

the.contrasts.1 <- c(
"Grp4aMinus4fMinus_vs_Grp4aPlus",
"Grp4aMinus4fMinus_vs_Grp4fPlus",
"Grp4aMinus4fMinus_vs_Cplus1Plus"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt2"),
    contrast=the.contrasts.1,
    annotation="download",
    org="mm10",
    refdb="ensembl",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_quantseq_run342b"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias",
        "biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","mm10")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)

the.contrasts.1 <- c(
"Cplus_vs_vectorhuh75"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt-hsa"),
    contrast=the.contrasts.1,
    annotation="download",
    org="hg19",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_quantseq_run342c"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias","biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","hg19")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)



#@ rerun with 'ingnored strandedness' bugfix
the.contrasts.1 <- c(
"Cplus_vs_vectorhuh75"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt-hsa"),
    contrast=the.contrasts.1,
    annotation="download",
    org="hg19",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_run_run342d"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias","biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","hg19")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)

the.contrasts.1 <- c(
	"Grp4aMinus_vs_Grp4aPlus",
	"Grp4fMinus_vs_Grp4fPlus"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt"),
    contrast=the.contrasts.1,
    annotation="download",
    org="mm10",
    refdb="ensembl",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_run_run342a"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias",
        "biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","mm10")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)


the.contrasts.1 <- c(
"Grp4aMinus4fMinus_vs_Grp4aPlus",
"Grp4aMinus4fMinus_vs_Grp4fPlus",
"Grp4aMinus4fMinus_vs_Cplus1Plus"
)

metaseqr(
    sample.list=file.path(the.path,"targets.txt2"),
    contrast=the.contrasts.1,
    annotation="download",
    org="mm10",
    refdb="ensembl",
    count.type="utr",
    normalization="deseq",
    statistics="deseq",
    fig.format=c("png","pdf"),
    export.where=file.path(the.path,"metaseqr_run_run342b"),
    restrict.cores=0.5,
    qc.plots=c(
        "mds","biodetection","countsbio","saturation","readnoise","filtered",
        "correl","pairwise","boxplot","gcbias","lengthbias",
        "biodist","volcano","deheatmap"
    ),
    exon.filters=NULL,
    gene.filters=list(
       length=list(
            length=500
        ),
        avg.reads=list(
            average.per.bp=100,
            quantile=0.25
        ),
        expression=list(
            median=TRUE,
            mean=FALSE,
            quantile=NA,
            known=NA,
            custom=NA
        ),
        biotype=get.defaults("biotype.filter","mm10")
    ),
    pcut=0.05,
    export.what=c("annotation","p.value","adj.p.value","fold.change",
		"counts","flags"),
    export.scale=c("log2","rpgm"),
    export.values="normalized",
    export.counts.table=TRUE,
	report.top=0.05
)