Merge pull request #694 from maxplanck-ie/dev_ksikora2

Dev ksikora2
maxplanck-ie · Sep 23, 2020 · e893b28 · e893b28
2 parents 4263be4 + 137fb07
commit e893b28
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diff --git a/conda-recipe/meta.yaml b/conda-recipe/meta.yaml
@@ -1,6 +1,6 @@
 package:
   name: snakepipes
-  version: 2.2.2
+  version: 2.2.3
 
 source:
   path: ../

diff --git a/docs/content/News.rst b/docs/content/News.rst
@@ -2,11 +2,12 @@ snakePipes News
 ===============
 
 
-snakePipes 2.x.y
+snakePipes 2.2.3
 ----------------
 
 * Genrich will now run if sampleSheet without replicates is provided.
 * Updated zenodo link to mouse genome GRCm38/mm10 .
+* Fixed start coordinates in Filtered results bed from CSAW.
 
 
 snakePipes 2.2.2

diff --git a/docs/content/setting_up.rst b/docs/content/setting_up.rst
@@ -34,7 +34,7 @@ The easiest way to install snakePipes is via our conda channel. The following co
 
 .. code:: bash
 
-    conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.2.2
+    conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.2.3
 
 This way, the software used within snakePipes do not conflict with the software pre-installed on your terminal or in your python environment.
 

diff --git a/snakePipes/__init__.py b/snakePipes/__init__.py
@@ -1 +1 @@
-__version__ = '2.2.2'
+__version__ = '2.2.3'
diff --git a/snakePipes/shared/cluster.yaml b/snakePipes/shared/cluster.yaml
@@ -1,5 +1,5 @@
 snakemake_latency_wait: 300
-snakemake_cluster_cmd: module load slurm; SlurmEasy --mem-per-cpu {cluster.memory} --threads {threads} --log {snakePipes_cluster_logDir} --name {rule}.snakemake
+snakemake_cluster_cmd: module load slurm; sbatch --ntasks-per-node 1 -p bioinfo --mem-per-cpu {cluster.memory} -c {threads} -e {snakePipes_cluster_logDir}/{rule}.%j.err -o {snakePipes_cluster_logDir}/{rule}.%j.out -J {rule}.snakemake
 snakePipes_cluster_logDir: cluster_logs
 __default__:
     memory: 1G

diff --git a/snakePipes/shared/rscripts/DB_functions.R b/snakePipes/shared/rscripts/DB_functions.R
@@ -339,6 +339,9 @@ writeOutput_chip <- function(chipResultObject, outfile_prefix, fdrcutoff,lfccuto
     full_res<-as.data.frame(merge(x=tabx,y=tabcom,by.x="name",by.y="name"),stringsAsFactors=FALSE) 
     full_res<-full_res[,c(2:ncol(full_res),1)]
     print(sprintf("Colnames of result file are %s",colnames(full_res)))
+    full_res[,2]<-full_res[,2]-1
+    full_res[,2]<-format(full_res[,2], scientific = FALSE)
+    full_res[,3]<-format(full_res[,3], scientific = FALSE)
     ##filter full result for FDR and LFC and write to output
     full_res.filt<-subset(full_res,(FDR<=fdrcutoff)&(abs(best.logFC)>=lfccutoff))
     if(nrow(full_res.filt)>0){

diff --git a/snakePipes/workflows/ChIP-seq/Snakefile b/snakePipes/workflows/ChIP-seq/Snakefile
@@ -143,7 +143,7 @@ def run_CSAW():
             file_list.append(["Annotation/genes.filtered.symbol","Annotation/genes.filtered.t2g","CSAW_{}_{}/CSAW.Stats_report.html".format(peakCaller, sample_name)])
             file_list.append([os.path.join("CSAW_{}_{}".format(peakCaller, sample_name), x) for x in list(itertools.chain.from_iterable([expand("CSAW.{change_dir}.cov.matrix",change_dir=change_direction),expand("CSAW.{change_dir}.cov.heatmap.png",change_dir=change_direction)]))])
             file_list.append([os.path.join("AnnotatedResults_{}_{}".format(peakCaller,sample_name), x) for x in list(itertools.chain.from_iterable([expand("Filtered.results.{change_dir}_withNearestGene.txt",change_dir=change_direction)]))])
-            if not useSpikeInForNorm:
+            if not useSpikeInForNorm and chip_samples_w_ctrl:
                 file_list.append([os.path.join("CSAW_{}_{}".format(peakCaller, sample_name), x) for x in list(itertools.chain.from_iterable([expand("CSAW.{change_dir}.log2r.matrix",change_dir=change_direction),expand("CSAW.{change_dir}.log2r.heatmap.png",change_dir=change_direction)]))])
         return( file_list )
     else:

diff --git a/snakePipes/workflows/ChIP-seq/internals.snakefile b/snakePipes/workflows/ChIP-seq/internals.snakefile
@@ -185,7 +185,9 @@ if sampleSheet:
     genrichDict = cf.sampleSheetGroups(sampleSheet)
     if chip_samples_w_ctrl:
         filtered_dict = filter_dict(sampleSheet,dict(zip(chip_samples_w_ctrl, [ get_control_name(x) for x in chip_samples_w_ctrl ])))
-        reordered_dict = {k: filtered_dict[k] for k in [item for sublist in genrichDict.values() for item in sublist]}
+    else:
+        filtered_dict = filter_dict(sampleSheet,dict(zip(chip_samples_wo_ctrl, [None]*len(chip_samples_wo_ctrl))))
+    reordered_dict = {k: filtered_dict[k] for k in [item for sublist in genrichDict.values() for item in sublist]}
 else:
     genrichDict = {"all_samples": chip_samples}