{"action":"created","comment":{"url":"https://api.github.com/repos/broadinstitute/picard/pulls/comments/48268962","id":48268962,"diff_hunk":"@@ -198,28 +217,39 @@ protected int doWork() {\n         }\n \n         // Construct and write the outputs\n-        final Histogram<Integer> histo = new Histogram<Integer>(\"coverage\", \"count\");\n+        final Histogram<Integer> depthHistogram = new Histogram<Integer>(\"coverage\", \"count\");\n         for (int i = 0; i < HistogramArray.length; ++i) {\n-            histo.increment(i, HistogramArray[i]);\n+            depthHistogram.increment(i, HistogramArray[i]);\n         }\n \n         // Construct and write the outputs\n-        final Histogram<Integer> baseQHisto = new Histogram<Integer>(\"value\", \"baseq_count\");\n+        final Histogram<Integer> baseQHistogram = new Histogram<Integer>(\"value\", \"baseq_count\");\n         for (int i=0; i<baseQHistogramArray.length; ++i) {\n-            baseQHisto.increment(i, baseQHistogramArray[i]);\n+            baseQHistogram.increment(i, baseQHistogramArray[i]);\n         }\n \n-        final WgsMetrics metrics = generateWgsMetrics();\n-        metrics.GENOME_TERRITORY = (long) histo.getSumOfValues();\n-        metrics.MEAN_COVERAGE = histo.getMean();\n-        metrics.SD_COVERAGE = histo.getStandardDeviation();\n-        metrics.MEDIAN_COVERAGE = histo.getMedian();\n-        metrics.MAD_COVERAGE = histo.getMedianAbsoluteDeviation();\n+        // Construct and write the outputs\n+        final Histogram<Integer> baseQHetHistogram = new Histogram<Integer>(\"value\", \"baseq_count\");\n+        final int BASEQ_MAX = 50;\n+        final Integer[] x = new Integer[50];","path":"src/java/picard/analysis/CollectWgsMetrics.java","position":103,"original_position":103,"commit_id":"c7954b8c680db3410f24a0cb12fa38fa300c75b7","original_commit_id":"c7954b8c680db3410f24a0cb12fa38fa300c75b7","user":{"login":"abaumann","id":755311,"avatar_url":"https://avatars.githubusercontent.com/u/755311?v=3","gravatar_id":"","url":"https://api.github.com/users/abaumann","html_url":"https://github.com/abaumann","followers_url":"https://api.github.com/users/abaumann/followers","following_url":"https://api.github.com/users/abaumann/following{/other_user}","gists_url":"https://api.github.com/users/abaumann/gists{/gist_id}","starred_url":"https://api.github.com/users/abaumann/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/abaumann/subscriptions","organizations_url":"https://api.github.com/users/abaumann/orgs","repos_url":"https://api.github.com/users/abaumann/repos","events_url":"https://api.github.com/users/abaumann/events{/privacy}","received_events_url":"https://api.github.com/users/abaumann/received_events","type":"User","site_admin":false},"body":"use BASEQ_MAX rather than 50","created_at":"2015-12-22T16:17:36Z","updated_at":"2015-12-22T16:17:36Z","html_url":"https://github.com/broadinstitute/picard/pull/355#discussion_r48268962","pull_request_url":"https://api.github.com/repos/broadinstitute/picard/pulls/355","_links":{"self":{"href":"https://api.github.com/repos/broadinstitute/picard/pulls/comments/48268962"},"html":{"href":"https://github.com/broadinstitute/picard/pull/355#discussion_r48268962"},"pull_request":{"href":"https://api.github.com/repos/broadinstitute/picard/pulls/355"}}},"pull_request":{"url":"https://api.github.com/repos/broadinstitute/picard/pulls/355","id":52900262,"html_url":"https://github.com/broadinstitute/picard/pull/355","diff_url":"https://github.com/broadinstitute/picard/pull/355.diff","patch_url":"https://github.com/broadinstitute/picard/pull/355.patch","issue_url":"https://api.github.com/repos/broadinstitute/picard/issues/355","number":355,"state":"open","locked":false,"title":"Add Theoretical Het SNP Sensitivity metric to picard tools","user":{"login":"kbergin","id":9449764,"avatar_url":"https://avatars.githubusercontent.com/u/9449764?v=3","gravatar_id":"","url":"https://api.github.com/users/kbergin","html_url":"https://github.com/kbergin","followers_url":"https://api.github.com/users/kbergin/followers","following_url":"https://api.github.com/users/kbergin/following{/other_user}","gists_url":"https://api.github.com/users/kbergin/gists{/gist_id}","starred_url":"https://api.github.com/users/kbergin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kbergin/subscriptions","organizations_url":"https://api.github.com/users/kbergin/orgs","repos_url":"https://api.github.com/users/kbergin/repos","events_url":"https://api.github.com/users/kbergin/events{/privacy}","received_events_url":"https://api.github.com/users/kbergin/received_events","type":"User","site_admin":false},"body":"Theoretical Het SNP Sensitivity and Het SNP Sensitivity Q Score metrics added to HS metrics, WGS metrics, Targeted PCR metrics, and Sampled WGS metrics (RapidQC). Added tests for each in Theoretical Het Test and added this metric to the respective tests for each collector. \r\n\r\nThe length of time added by the calculation of the Theoretical Het Sensitivity metrics is laid out in the table below. These times are from running the unit tests on full sized metrics files in IntelliJ with -Xmx1G as a VM setting. The part that takes the longest is the random sampling. In the standard settings in the code it performs 10,000 samplings, which takes longer with less data in the targeted metrics. 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