diff --git a/deeptools/countReadsPerBin.py b/deeptools/countReadsPerBin.py
index 1b971914ef..17b727d6de 100644
--- a/deeptools/countReadsPerBin.py
+++ b/deeptools/countReadsPerBin.py
@@ -10,6 +10,7 @@
 from deeptools import bamHandler
 from deeptools import mapReduce
 from deeptoolsintervals import GTF
+import pyBigWig
 
 debug = 0
 old_settings = np.seterr(all='ignore')
@@ -235,7 +236,13 @@ def run(self, allArgs=None):
         # workers for analysis. If too short, too much time is spend loading the files
         # if too long, some processors end up free.
         # the following values are empirical
-        bamFilesHandlers = [bamHandler.openBam(x) for x in self.bamFilesList]
+        bamFilesHandlers = []
+        for x in self.bamFilesList:
+            try:
+                y = bamHandler.openBam(x)
+            except:
+                y = pyBigWig.open(x)
+            bamFilesHandlers.append(y)
         chromSizes, non_common = deeptools.utilities.getCommonChrNames(bamFilesHandlers, verbose=self.verbose)
 
         # skip chromosome in the list. This is usually for the
@@ -263,14 +270,28 @@ def run(self, allArgs=None):
             min_num_of_samples = int(genomeSize / np.mean(chrLengths))
             raise ValueError("numberOfSamples has to be bigger than {} ".format(min_num_of_samples))
 
-        max_mapped = max([x.mapped for x in bamFilesHandlers])
-
-        reads_per_bp = float(max_mapped) / genomeSize
-        # chunkSize =  int(100 / ( reads_per_bp  * len(bamFilesList)) )
-
-        chunkSize = int(self.stepSize * 1e3 / (reads_per_bp * len(bamFilesHandlers)))
+        max_mapped = []
+        for x in bamFilesHandlers:
+            try:
+                max_mapped.append(x.mapped)
+            except:
+                # bigWig, use a fixed value
+                max_mapped.append(0)
+        max_mapped = max(max_mapped)
+
+        # If max_mapped is 0 (i.e., bigWig input), set chunkSize to a multiple of binLength and use every bin
+        if max_mapped == 0:
+            chunkSize = 10000 * self.binLength
+            self.stepSize = self.binLength
+        else:
+            reads_per_bp = float(max_mapped) / genomeSize
+            chunkSize = int(self.stepSize * 1e3 / (reads_per_bp * len(bamFilesHandlers)))
         [bam_h.close() for bam_h in bamFilesHandlers]
 
+        # Ensure that chunkSize is always at least self.stepSize
+        if chunkSize < self.stepSize:
+            chunkSize = self.stepSize
+
         if self.verbose:
             print("step size is {}".format(self.stepSize))
 
@@ -388,7 +409,12 @@ def count_reads_in_region(self, chrom, start, end, bed_regions_list=None):
 
         start_time = time.time()
 
-        bam_handlers = [bamHandler.openBam(bam) for bam in self.bamFilesList]
+        bam_handlers = []
+        for fname in self.bamFilesList:
+            try:
+                bam_handlers.append(bamHandler.openBam(fname))
+            except:
+                bam_handlers.append(pyBigWig.open(fname))
 
         blackList = None
         if self.blackListFileName is not None:
@@ -537,11 +563,22 @@ def get_coverage_of_region(self, bamHandle, chrom, regions,
             start_time = time.time()
             # caching seems faster. TODO: profile the function
             c = 0
-            if chrom in bamHandle.references:
-                reads = [r for r in bamHandle.fetch(chrom, regStart, regEnd)
-                         if r.flag & 4 == 0]
-            else:
-                raise NameError("chromosome {} not found in bam file".format(chrom))
+            try:
+                # BAM input
+                if chrom in bamHandle.references:
+                    reads = [r for r in bamHandle.fetch(chrom, regStart, regEnd)
+                             if r.flag & 4 == 0]
+                else:
+                    raise NameError("chromosome {} not found in bam file".format(chrom))
+            except:
+                # bigWig input, as used by plotFingerprint
+                if bamHandle.chroms(chrom):
+                    _ = np.array(bamHandle.stats(chrom, regStart, regEnd, type="mean", nBins=nRegBins), dtype=np.float)
+                    _[np.isnan(_)] = 0.0
+                    coverages += _
+                    continue
+                else:
+                    raise NameError("chromosome {} not found in bigWig file with chroms {}".format(chrom, bamHandle.chroms()))
 
             prev_start_pos = None  # to store the start positions
             # of previous processed read pair
diff --git a/deeptools/plotFingerprint.py b/deeptools/plotFingerprint.py
index 1dbdb48143..abf40c9d01 100644
--- a/deeptools/plotFingerprint.py
+++ b/deeptools/plotFingerprint.py
@@ -318,7 +318,7 @@ def signalAndBinDist(x):
 
     # Compute the JSD from the PMFs
     M = (PMFinput + PMFchip) / 2.0
-    JSD = 0.5 * (np.sum(PMFinput * np.log2(PMFinput / M))) + 0.5 * (np.sum(PMFchip * np.log2(PMFchip / M)))
+    JSD = 0.5 * (np.nansum(PMFinput * np.log2(PMFinput / M))) + 0.5 * (np.nansum(PMFchip * np.log2(PMFchip / M)))
 
     return np.sqrt(JSD)
 
@@ -424,5 +424,6 @@ def main(args=None):
             args.outQualityMetrics.write("\n")
         args.outQualityMetrics.close()
 
+
 if __name__ == "__main__":
     main()
diff --git a/deeptools/utilities.py b/deeptools/utilities.py
index d4b0865bd2..013b4ab56e 100644
--- a/deeptools/utilities.py
+++ b/deeptools/utilities.py
@@ -107,8 +107,12 @@ def get_chrom_and_size(bam_handler):
         :param bam_handler:
         :return: list of (chrom, size) tuples
         """
-        return [(bam_handler.references[i], bam_handler.lengths[i])
-                for i in range(0, len(bam_handler.references))]
+        try:
+            # BAM file
+            return [(bam_handler.references[i], bam_handler.lengths[i])
+                    for i in range(0, len(bam_handler.references))]
+        except:
+            return [(k, v) for k, v in bam_handler.chroms().items()]
 
     def print_chr_names_and_size(chr_set):
         sys.stderr.write("chromosome\tlength\n")