Remove unnecessary whitespaces

Snakefile

 """
 Authors: Sam Nooij
 Organisation: Leiden University Medical Centre (LUMC)
-Department: Medical Microbiology (MM) Research, 
+Department: Medical Microbiology (MM) Research,
     Center for Microbiome Analyses and Therapeutics (CMAT)
 Date: 2020-03-20
 
@@ -10,7 +10,7 @@ Specifically for screening for genes of interest and their species
 of origin.
 
 Input: Jovian's output (classified scaffolds and trimmed reads)
-Output: report on presence and abundance of species and 
+Output: report on presence and abundance of species and
     genes of interest
 
 Example use:
@@ -18,7 +18,7 @@ Example use:
 Or on the Shark cluster:
     $ snakemake --use-conda --latency-wait 60 --jobs 16 \
     --cluster "qsub -q all.q -pe BWA {threads} -l h_vmem={cluster.vmem} -cwd -j Y -o log/cluster/ -V" \
-    --cluster-config config/cluster_config.yaml 
+    --cluster-config config/cluster_config.yaml
 Or with SLURM:
     $ snakemake -p --use-conda --latency-wait 60 --jobs 10 \
     --cluster "sbatch --parsable -J Snakejob-{name}.{jobid} -N 1 -n {threads} --mem={cluster.vmem} -t {cluster.time} -D . -e log/SLURM/{name}-{jobid}.err -o log/SLURM/{name}-{jobid}.out" \
@@ -74,7 +74,7 @@ else:
 
 rule all:
    input:
-        expand("data/tmp/all_taxClassified-{species}.tsv", 
+        expand("data/tmp/all_taxClassified-{species}.tsv",
                species = SPECIES),
         #Filtered table for species of interest
 
@@ -92,7 +92,7 @@ rule all:
                species = SPECIES, ext = ["png", "pdf"]),
         #pyANI Average Nucleotide Identity plots for each species
 
-        expand(REFERENCE_DIR + "{ref}.blastdb.{ext}", 
+        expand(REFERENCE_DIR + "{ref}.blastdb.{ext}",
                ref = REFERENCE_NAMES, ext = ["nhr", "nin", "nsq"]),
         #Blast database files for each reference
 
@@ -138,7 +138,7 @@ rule all:
         "data/processed/Depth_of_coverage.tsv",
         #Concatenated tables with depth of coverage
 
-        
+
 ### Step 3: include processing steps to generate output ###
 
 ## First, filter out species of interest ##