0.6.0 release document updates.

PiperOrigin-RevId: 191805185
google · Apr 10, 2018 · fce4ee3 · fce4ee3
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diff --git a/docs/deepvariant-case-study.md b/docs/deepvariant-case-study.md
@@ -40,9 +40,9 @@ Set a number of shell variables, to make what follows easier to read.
 ```bash
 BASE="${HOME}/case-study"
 BUCKET="gs://deepvariant"
-BIN_VERSION="0.5.1"
-MODEL_VERSION="0.5.0"
-MODEL_CL="182548131"
+BIN_VERSION="0.6.0"
+MODEL_VERSION="0.6.0"
+MODEL_CL="191676894"
 
 # Note that we don't specify the CL number for the binary, only the bin version.
 BIN_BUCKET="${BUCKET}/binaries/DeepVariant/${BIN_VERSION}/DeepVariant-${BIN_VERSION}+cl-*"
@@ -260,11 +260,11 @@ the postprocess\_variants step, so the full call would look instead like:
 
 Step                               | wall time
 ---------------------------------- | -------------
-`make_examples`                    | 5h 37m 42s
-`call_variants`                    | 11h 0m 29s
-`postprocess_variants` (no gVCF)   | 21m 54s
-`postprocess_variants` (with gVCF) | 58m 24s
-total time (single machine)        | 17h - 17h 36m
+`make_examples`                    | 5h 27m 24s
+`call_variants`                    | 11h 11m 53s
+`postprocess_variants` (no gVCF)   | 21m 5s
+`postprocess_variants` (with gVCF) | 58m 51s
+total time (single machine)        | 17h - 17h 38m
 
 ## Variant call quality
 
@@ -297,5 +297,5 @@ pkrusche/hap.py /opt/hap.py/bin/hap.py \
 
 Type  | # FN | # FP | Recall   | Precision | F1\_Score
 ----- | ---- | ---- | -------- | --------- | ---------
-INDEL | 2116 | 1066 | 0.995447 | 0.997794  | 0.996619
-SNP   | 1684 | 916  | 0.999447 | 0.999699  | 0.999573
+INDEL | 1505 | 1133 | 0.996762 | 0.997660  | 0.997211
+SNP   | 1526 | 933  | 0.999499 | 0.999694  | 0.999597
diff --git a/docs/deepvariant-exome-case-study.md b/docs/deepvariant-exome-case-study.md
@@ -22,9 +22,9 @@ Set a number of shell variables, to make what follows easier to read.
 ```bash
 BASE="${HOME}/exome-case-study"
 BUCKET="gs://deepvariant"
-BIN_VERSION="0.5.1"
-MODEL_VERSION="0.5.0"
-MODEL_CL="181413382"
+BIN_VERSION="0.6.0"
+MODEL_VERSION="0.6.0"
+MODEL_CL="191676894"
 
 # Note that we don't specify the CL number for the binary, only the bin version.
 BIN_BUCKET="${BUCKET}/binaries/DeepVariant/${BIN_VERSION}/DeepVariant-${BIN_VERSION}+cl-*"
@@ -213,11 +213,11 @@ study](deepvariant-case-study.md#run_postprocess_variants).
 
 Step                               | wall time
 ---------------------------------- | ---------
-`make_examples`                    | 69m 22s
-`call_variants`                    | 6m 32s
+`make_examples`                    | 65m 45s
+`call_variants`                    | 6m 21s
 `postprocess_variants` (no gVCF)   | 0m 13s
-`postprocess_variants` (with gVCF) | 0m 41s
-total time (single machine)        | ~ 1h 16m
+`postprocess_variants` (with gVCF) | 1m 24s
+total time (single machine)        | ~ 1h 13m
 
 ## Variant call quality
 
@@ -260,8 +260,8 @@ Here are the results:
 
 Type  | # FN | # FP | Recall   | Precision | F1\_Score
 ----- | ---- | ---- | -------- | --------- | ---------
-INDEL | 140  | 51   | 0.946154 | 0.979898  | 0.962730
-SNP   | 45   | 24   | 0.998666 | 0.999288  | 0.998977
+INDEL | 127  | 35   | 0.951154 | 0.986193  | 0.968357
+SNP   | 43   | 26   | 0.998725 | 0.999229  | 0.998977
 
 ## Separate models for calling whole genome and exome data
 

diff --git a/docs/deepvariant-quick-start.md b/docs/deepvariant-quick-start.md
@@ -66,9 +66,9 @@ The DeepVariant binaries can be downloaded to your instance with the
 
 ```bash
 BUCKET="gs://deepvariant"
-BIN_VERSION="0.5.1"
-MODEL_VERSION="0.5.0"
-MODEL_CL="182548131"
+BIN_VERSION="0.6.0"
+MODEL_VERSION="0.6.0"
+MODEL_CL="191676894"
 
 # Note that we don't specify the CL number for the binary, only the bin version.
 BIN_BUCKET="${BUCKET}/binaries/DeepVariant/${BIN_VERSION}/DeepVariant-${BIN_VERSION}+cl-*"
@@ -117,13 +117,13 @@ In this bucket models are organized into subdirectories by program name and
 version, such as for the model to run on whole genome sequencing data:
 
 ```
-DeepVariant/0.5.0/DeepVariant-inception_v3-0.5.0+cl-182548131.data-wgs_standard/
+DeepVariant/0.6.0/DeepVariant-inception_v3-0.6.0+cl-191676894.data-wgs_standard/
 ```
 
 and for the model to run on whole exome sequencing data.
 
 ```
-DeepVariant/0.5.0/DeepVariant-inception_v3-0.5.0+cl-181413382.data-wes_standard/
+DeepVariant/0.6.0/DeepVariant-inception_v3-0.6.0+cl-191676894.data-wes_standard/
 ```
 
 The model files are tagged with the program name and version, model name and the
@@ -322,10 +322,10 @@ sudo docker pull pkrusche/hap.py
 sudo docker run -it -v `pwd`:/data pkrusche/hap.py /opt/hap.py/bin/hap.py \
   /data/quickstart-testdata/test_nist.b37_chr20_100kbp_at_10mb.vcf.gz \
   "/data/${FINAL_OUTPUT_VCF}" \
-  --preprocess-truth \
   -f /data/quickstart-testdata/test_nist.b37_chr20_100kbp_at_10mb.bed \
   -r "/data/${REF}" \
   -o "/data/${OUTPUT_DIR}/happy.output" \
+  --engine=vcfeval \
   -l chr20:10000000-10010000
 ```
 
@@ -334,8 +334,8 @@ You should see output similar to the following.
 ```
 Benchmarking Summary:
   Type Filter  TRUTH.TOTAL  TRUTH.TP  TRUTH.FN  QUERY.TOTAL  QUERY.FP  QUERY.UNK  FP.gt  METRIC.Recall  METRIC.Precision  METRIC.Frac_NA  METRIC.F1_Score  TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
- INDEL    ALL            4         4         0           14         0         10      0              1                 1        0.714286                1                     NaN                     NaN                   0.333333                   1.166667
- INDEL   PASS            4         4         0           14         0         10      0              1                 1        0.714286                1                     NaN                     NaN                   0.333333                   1.166667
-   SNP    ALL           44        44         0           60         0         16      0              1                 1        0.266667                1                     1.2                1.307692                   0.333333                   0.395349
-   SNP   PASS           44        44         0           60         0         16      0              1                 1        0.266667                1                     1.2                1.307692                   0.333333                   0.395349
+ INDEL    ALL            4         4         0           13         0          9      0              1                 1        0.692308                1                     NaN                     NaN                   0.333333                   1.000000
+ INDEL   PASS            4         4         0           13         0          9      0              1                 1        0.692308                1                     NaN                     NaN                   0.333333                   1.000000
+   SNP    ALL           44        44         0           60         0         16      0              1                 1        0.266667                1                     1.2                1.307692                   0.333333                   0.363636
+   SNP   PASS           44        44         0           60         0         16      0              1                 1        0.266667                1                     1.2                1.307692                   0.333333                   0.363636
 ```