diff --git a/algo/core/segment.cpp b/algo/core/segment.cpp
index 3b5fd5c435a1270aaf8a2b6b23dd5d4355096c81..7c84cc57942d236215dee3e3d67bff64f1d44232 100644
--- a/algo/core/segment.cpp
+++ b/algo/core/segment.cpp
@@ -326,7 +326,8 @@ KmerSegmenter::~KmerSegmenter() {
     delete kaa;
 }
 
-KmerMultiSegmenter::KmerMultiSegmenter(Sequence seq, MultiGermline *multigermline, ostream *out_unsegmented, double threshold)
+KmerMultiSegmenter::KmerMultiSegmenter(Sequence seq, MultiGermline *multigermline, ostream *out_unsegmented,
+                                       double threshold, int nb_reads_for_evalue)
 {
   int best_score_seg = 0 ; // Best score, segmented sequences
   int best_score_unseg = 0 ; // Best score, unsegmented sequences
@@ -396,9 +397,9 @@ KmerMultiSegmenter::KmerMultiSegmenter(Sequence seq, MultiGermline *multigermlin
   if (threshold_nb_expected > NO_LIMIT_VALUE)
     if (the_kseg->isSegmented()) {
         // the_kseg->evalue also depends on the number of germlines from the *Multi*KmerSegmenter
-        the_kseg->evalue = getNbExpected();
+        the_kseg->evalue = getNbExpected(nb_reads_for_evalue);
 
-        pair <double, double> p = getNbExpectedLeftRight();
+        pair <double, double> p = getNbExpectedLeftRight(nb_reads_for_evalue);
         the_kseg->evalue_left = p.first;
         the_kseg->evalue_right = p.second;
 
@@ -414,14 +415,14 @@ KmerMultiSegmenter::KmerMultiSegmenter(Sequence seq, MultiGermline *multigermlin
       }
 }
 
-double KmerMultiSegmenter::getNbExpected() const {
-  pair <double, double> p = getNbExpectedLeftRight();
+double KmerMultiSegmenter::getNbExpected(int multiplier) const {
+  pair <double, double> p = getNbExpectedLeftRight(multiplier);
   return (p.first + p.second);
 }
 
-pair<double,double> KmerMultiSegmenter::getNbExpectedLeftRight() const {
+pair<double,double> KmerMultiSegmenter::getNbExpectedLeftRight(int multiplier) const {
   pair <double, double> p = the_kseg->getKmerAffectAnalyser()->getLeftRightProbabilityAtLeastOrAbove();
-  return pair<double, double>(p.first * multi_germline->germlines.size(), p.second * multi_germline->germlines.size());
+  return pair<double, double>(p.first * multiplier * multi_germline->germlines.size(), p.second * multiplier * multi_germline->germlines.size());
 }
 
 KmerMultiSegmenter::~KmerMultiSegmenter() {
diff --git a/algo/core/segment.h b/algo/core/segment.h
index ff5a4ca27986bd35150c228d793c8c4ab7932927..8e7618869026da984fe47712011f35ce6ef3bb2b 100644
--- a/algo/core/segment.h
+++ b/algo/core/segment.h
@@ -207,18 +207,18 @@ class KmerMultiSegmenter
    * @param threshold: threshold of randomly expected segmentation
    */
   KmerMultiSegmenter(Sequence seq, MultiGermline *multigermline, ostream *out_unsegmented,
-                     double threshold = THRESHOLD_NB_EXPECTED);
+                     double threshold = THRESHOLD_NB_EXPECTED, int nb_reads_for_evalue = 1);
 
   /**
    * @return expected number of Segmenter that would have yield the maximum score by chance
    */
-  double getNbExpected() const;
+  double getNbExpected(int multiplier) const;
 
   /**
    * @return expected number of Segmenter that would have yield the maximum score by chance
    *         on the left part of the read and on the right part of the read respectively.
    */
-  pair<double,double> getNbExpectedLeftRight() const;
+  pair<double,double> getNbExpectedLeftRight(int multiplier) const;
 
   ~KmerMultiSegmenter();
 
diff --git a/algo/core/windowExtractor.cpp b/algo/core/windowExtractor.cpp
index a955e11cf8e7850e93aee7e8c26856a692ee7fe2..92de05c1b25b1f3b1ead7287d6431dcec15cdca7 100644
--- a/algo/core/windowExtractor.cpp
+++ b/algo/core/windowExtractor.cpp
@@ -11,7 +11,7 @@ WindowsStorage *WindowExtractor::extract(OnlineFasta *reads, MultiGermline *mult
 					 size_t w,
                                          map<string, string> &windows_labels,
                                          int stop_after, int only_nth_read, bool keep_unsegmented_as_clone,
-                                         double nb_expected) {
+                                         double nb_expected, int nb_reads_for_evalue) {
   init_stats();
 
   WindowsStorage *windowsStorage = new WindowsStorage(windows_labels);
@@ -38,7 +38,7 @@ WindowsStorage *WindowExtractor::extract(OnlineFasta *reads, MultiGermline *mult
       *out_affects << reads->getSequence();
     }
     
-    KmerMultiSegmenter kmseg(reads->getSequence(), multigermline, out_affects, nb_expected);
+    KmerMultiSegmenter kmseg(reads->getSequence(), multigermline, out_affects, nb_expected, nb_reads_for_evalue);
     
     KmerSegmenter *seg = kmseg.the_kseg ;
     int read_length = seg->getSequence().sequence.length();
diff --git a/algo/core/windowExtractor.h b/algo/core/windowExtractor.h
index c65b73c3b867578d28b86bed1bea618614dba78e..6c834b5831c769645c2cef066ef6b1c0e57eb0f8 100644
--- a/algo/core/windowExtractor.h
+++ b/algo/core/windowExtractor.h
@@ -40,6 +40,7 @@ class WindowExtractor {
    * @param w: length of the window
    * @param windows_labels: Windows that must be kept and registered as such.
    * @param nb_expected: maximal e-value of the segmentation
+   * @param nb_reads_for_evalue: number of reads, used for e-value computation. Can be approximate or faked.
    * @return a pointer to a WindowsStorage that will contain all the windows.
    *         It is a pointer so that the WindowsStorage is not duplicated.
    * @post Statistics on segmentation will be provided through the getSegmentationStats() methods
@@ -49,7 +50,7 @@ class WindowExtractor {
                           size_t w,
                           map<string, string> &windows_labels,
                           int stop_after=-1, int only_nth_reads=1, bool keep_unsegmented_as_clone=false,
-                          double nb_expected = THRESHOLD_NB_EXPECTED);
+                          double nb_expected = THRESHOLD_NB_EXPECTED, int nb_reads_for_evalue = 1);
 
   /**
    * @return the average length of sequences whose segmentation has been classified as seg