Revert "Merge branch 'rework-tests' into 'master'"

This reverts merge request !89

jass/test/data_test1/COV.csv

+ID	z_DISNEY_RATATOUY	z_DISNEY_POCAHONT
+z_DISNEY_RATATOUY	2.05403006060606	0.394332909090909
+z_DISNEY_POCAHONT	0.394332909090909	1.17729254545455

jass/test/data_test1/SumStatTab.txt

+rsid	position	chr	region	Z_ratatouy	Z_pocahont
+rs1	1	1	1	0.812	-1.06
+rs2	2	1	1	2.197	0.937
+rs3	3	1	2	2.049	0.854
+rs4	1	2	3	1.632	1.461
+rs5	2	2	3	0.254	-1.413
+rs6	3	2	4	0.491	0.567
+rs7	4	2	4	-0.324	0.583
+rs8	5	2	4	-1.662	-1.307
+rs9	1	3	5	1.768	-0.54
+rs10	2	3	5	0.026	1.948
+rs11	3	3	6	1.129	0.054
+rs12	4	3	7	-2.38	0.352

jass/test/data_test1/metadata.txt

+information	content
+title	Mock dataset with disney
+description	"lorem ipsum"
+ancestry	DIS
+assembly	dSNY

jass/test/data_test1/regions.txt

+chr	start	stop
+chr1	1	2
+chr1	3	4
+chr2	1	2
+chr2	3	5
+chr3	1	2
+chr3	3	3
+chr3	4	4

jass/test/data_test1/summary.csv

+Outcome	FullName	Consortium	Type	Reference	ReferenceLink	dataLink	internalDataLink	Nsample	Ncase	Ncontrol
+RATATOUY	Ratatouille ou la mort de l'hygiène en cuisine	DISNEY	BrainWashing	Courgette et al., 1754	http://www.marmiton.org/recettes/recette_ratatouille_23223.asp	pouet	pouet	1000000		
+POCAHONT	Pocahontas mange des tapas	DISNEY	BrainWashing	Rolfe et al., 1614	https://fr.wikipedia.org/wiki/Pocahontas	Gargar	Gargar	1000000		

jass/test/data_test1/z_DISNEY_POCAHONT_chr1.txt

+rsid	position	refAllele	altAllele	Z
+rs1	1	C	T	-1.06
+rs2	2	G	T	0.937
+rs3	3	C	T	0.854

jass/test/data_test1/z_DISNEY_POCAHONT_chr2.txt

+rsid	position	refAllele	altAllele	Z
+rs4	1	G	T	1.461
+rs5	2	A	T	-1.413
+rs6	3	A	C	0.567
+rs7	4	A	G	0.583
+rs8	5	C	G	-1.307

jass/test/data_test1/z_DISNEY_POCAHONT_chr3.txt

+rsid	position	refAllele	altAllele	Z
+rs9	1	C	T	-0.54
+rs10	2	G	T	1.948
+rs11	3	A	C	0.054
+rs12	4	A	C	0.352

jass/test/data_test1/z_DISNEY_RATATOUY_chr1.txt

+rsid	position	refAllele	altAllele	Z
+rs1	1	C	T	0.812
+rs2	2	G	T	2.197
+rs3	3	C	T	2.049

jass/test/data_test1/z_DISNEY_RATATOUY_chr2.txt

+rsid	position	refAllele	altAllele	Z
+rs4	1	G	T	1.632
+rs5	2	A	T	0.254
+rs6	3	A	C	0.491
+rs7	4	A	G	-0.324
+rs8	5	C	G	-1.662

jass/test/data_test1/z_DISNEY_RATATOUY_chr3.txt

+rsid	position	refAllele	altAllele	Z
+rs9	1	C	T	1.768
+rs10	2	G	T	0.026
+rs11	3	A	C	1.129
+rs12	4	A	C	-2.38

jass/test/data_test2/COV.csv

+ID	z_BMW_ISETTA	z_BMW_MINI	z_FIAT_CINQCENT	z_FIAT_CINQUECENTO	z_MERCO_SMART	z_TATA_TATANANO
+z_BMW_ISETTA	2	1	1	1	1	1
+z_BMW_MINI	1	2	1	1	1	1
+z_FIAT_CINQCENT	1	1	2	1	1	1
+z_FIAT_CINQUECENTO	1	1	1	2	1	1
+z_MERCO_SMART	1	1	1	1	2	1
+z_TATA_TATANANO	1	1	1	1	1	2

jass/test/data_test2/create_unit_test_smart.R

+## There 6 phenotypes
+sumtab <- read.table("summary.txt", sep="\t", header=TRUE, stringsAsFactors = FALSE)
+## Zscore ID: z_CONSORITUM_PHENOTYPE_chr#chr.txt
+ids <- sprintf("z_%s_%s",sumtab$Consortium, sumtab$Outcome)
+## The covariance is set to 1 and the variance to 2
+COV <- toeplitz(c(2,1,1,1,1,1))
+rownames(COV) <- colnames(COV) <- ids
+
+
+## Structure:
+# - 5 chromosomes, 2 regions per chromosomes
+# - 10 regions, 2 regions per chromosome
+# - 30 SNPs, 3 SNPs per region
+
+## Structure of missing values region per region ;
+##   ".." means no missing values
+##   "XX" means the whole region is missing
+#
+#      Z1 Z2 Z3 Z4 Z5 Z6
+# R1   .. .. .. .. .. ..
+# R2   .. .. .. .. .. ..
+# R3   XX .. .. .. .. ..
+# R4   .. XX .. .. .. .. 
+# R5   .. .. XX .. .. ..
+# R6   .. .. .. XX .. ..
+# R7   .. .. .. .. XX ..
+# R8   .. .. .. .. .. XX
+# R9   XX XX XX .. .. .. 
+# R10  .. .. .. XX XX XX
+filenames <- paste0(rep(ids,e=5), "_chr", rep(1:5, 6), ".txt")
+
+## rsid : rs_#chr_#region_#snp
+rsid <- paste0("rs", "_chr", rep(1:5, e=6), # chr
+               "_reg", sprintf("%02i", rep(1:10, e=3)), # region
+               "_", sprintf("%02i", 1:30)) # snp
+pos <- rep(1:6, 5)
+chr <- rep(1:5, e=6)
+reg <- rep(1:10, e=3)
+ref <- "A"
+alt <- "G"
+BIGZ <- matrix(1:(30*6), 30, 6)
+BIGZ[grep("reg03", rsid),1] <- NA
+BIGZ[grep("reg04", rsid),2] <- NA
+BIGZ[grep("reg05", rsid),3] <- NA
+BIGZ[grep("reg06", rsid),4] <- NA
+BIGZ[grep("reg07", rsid),5] <- NA
+BIGZ[grep("reg08", rsid),6] <- NA
+BIGZ[grep("reg09", rsid),1:3] <- NA
+BIGZ[grep("reg10", rsid),4:6] <- NA
+rownames(BIGZ) <- rsid
+
+# What does it look like ?
+require(pheatmap)
+png("zscores.png", res = 100)
+pheatmap(BIGZ, cluster_rows = FALSE, cluster_cols = FALSE, cellwidth = 10, cellheight = 10)
+dev.off()
+# Create regions
+
+# Create Z scores
+
+
+# Write covariance matrix
+write.table(data.frame(ID=ids, COV), file="COV.csv", row.names = F, quote=F, sep="\t")
+
+# Write region file
+regions <- data.frame(chr=sprintf("chr%i", rep(1:5,e=2)),
+                      start=rep(c(1,4),5),
+                      stop=rep(c(3,6),5))
+write.table(regions, file="regions.txt", row.names = F, quote=F, sep="\t")
+# Write all the Z files
+k <- 1
+for (j in 1:6) {
+  for (chrnum in 1:5) {
+    ind <- grep(sprintf("chr%i", chrnum), rsid)
+    tmp <- data.frame(rsid = rsid[ind], 
+                      pos = pos[ind],
+                      ref=ref,
+                      alt=alt,
+                      Zscore=unname(BIGZ[ind, j]))
+    write.table(na.omit(tmp), file = filenames[k], quote=FALSE)
+    k <- k+1
+  }
+}
+
+# Compute the summary statistic
+
+