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Update all case studies for v1.6.1 release
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kishwarshafin committed Mar 18, 2024
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2 changes: 1 addition & 1 deletion .github/ISSUE_TEMPLATE/problem_report.md
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Expand Up @@ -7,7 +7,7 @@ assignees: ''

---

**Have you checked the FAQ? https://github.com/google/deepvariant/blob/r1.6/docs/FAQ.md**:
**Have you checked the FAQ? https://github.com/google/deepvariant/blob/r1.6.1/docs/FAQ.md**:

**Describe the issue:**
(A clear and concise description of what the issue is.)
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2 changes: 1 addition & 1 deletion .github/ISSUE_TEMPLATE/question.md
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Expand Up @@ -7,6 +7,6 @@ assignees: ''

---

**Have you checked the FAQ? https://github.com/google/deepvariant/blob/r1.6/docs/FAQ.md**:
**Have you checked the FAQ? https://github.com/google/deepvariant/blob/r1.6.1/docs/FAQ.md**:


4 changes: 2 additions & 2 deletions README.md
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@@ -1,6 +1,6 @@
<img src="docs/images/dv_logo.png" width=50% height=50%>

[![release](https://img.shields.io/badge/release-v1.6.0-green?logo=github)](https://github.com/google/deepvariant/releases)
[![release](https://img.shields.io/badge/release-v1.6.1-green?logo=github)](https://github.com/google/deepvariant/releases)
[![announcements](https://img.shields.io/badge/announcements-blue)](https://groups.google.com/d/forum/deepvariant-announcements)
[![blog](https://img.shields.io/badge/blog-orange)](https://goo.gl/deepvariant)

Expand Down Expand Up @@ -70,7 +70,7 @@ Please also note:
We recommend using our Docker solution. The command will look like this:

```
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"
docker run \
-v "YOUR_INPUT_DIR":"/input" \
-v "YOUR_OUTPUT_DIR:/output" \
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6 changes: 3 additions & 3 deletions docs/FAQ.md
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Expand Up @@ -143,7 +143,7 @@ container, you can `ls` inside the container. For example, using the setup shown
in the README and looking inside the `/input` volume:

```
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"
docker run \
-v "YOUR_INPUT_DIR":"/input" \
-v "YOUR_OUTPUT_DIR:/output" \
Expand All @@ -158,7 +158,7 @@ and outside the Docker container.
```
echo $HOME # see what your home directory is first.
ls $HOME
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"
sudo docker run \
-v "${HOME}":"${HOME}" \
google/deepvariant:"${BIN_VERSION}" \
Expand All @@ -171,7 +171,7 @@ Since the DeepVariant v0.9 release, we recommend
"[Best practices for multi-sample variant calling with DeepVariant](https://github.com/google/deepvariant/blob/r0.9/docs/trio-merge-case-study.md)".

For specifically calling on duos or trios, we introduced
[DeepTrio](https://github.com/google/deepvariant/blob/r1.6/docs/deeptrio-details.md)
[DeepTrio](https://github.com/google/deepvariant/blob/r1.6.1/docs/deeptrio-details.md)
in v1.1.

## Why am I seeing "CUDA_ERROR_NOT_INITIALIZED: initialization error" while running on GPU?
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2 changes: 1 addition & 1 deletion docs/deeptrio-pacbio-case-study.md
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Expand Up @@ -85,7 +85,7 @@ is run as a separate command.
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo apt -y update
sudo apt-get -y install docker.io
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4 changes: 2 additions & 2 deletions docs/deeptrio-quick-start.md
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Expand Up @@ -32,7 +32,7 @@ documentation on how to build.
### Get Docker image

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo apt -y update
sudo apt-get -y install docker.io
Expand Down Expand Up @@ -341,7 +341,7 @@ INDEL PASS 2 2 0 2 0 0
[BAM]: http://genome.sph.umich.edu/wiki/BAM
[BWA]: https://academic.oup.com/bioinformatics/article/25/14/1754/225615/Fast-and-accurate-short-read-alignment-with
[docker build]: https://docs.docker.com/engine/reference/commandline/build/
[Dockerfile]: https://github.com/google/deepvariant/blob/r1.6/Dockerfile.deeptrio
[Dockerfile]: https://github.com/google/deepvariant/blob/r1.6.1/Dockerfile.deeptrio
[FASTA]: https://en.wikipedia.org/wiki/FASTA_format
[VCF]: https://samtools.github.io/hts-specs/VCFv4.3.pdf
[run_deeptrio.py]: ../scripts/run_deeptrio.py
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2 changes: 1 addition & 1 deletion docs/deeptrio-wgs-case-study.md
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Expand Up @@ -82,7 +82,7 @@ command.
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker pull google/deepvariant:deeptrio-"${BIN_VERSION}"

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2 changes: 1 addition & 1 deletion docs/deepvariant-case-study.md
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Expand Up @@ -67,7 +67,7 @@ DeepVariant pipeline consists of 3 steps: `make_examples`, `call_variants`, and
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${PWD}/input":"/input" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-complete-g400-case-study.md
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Expand Up @@ -52,7 +52,7 @@ On a CPU-only machine:
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0rc4"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${PWD}/input":"/input" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-complete-t7-case-study.md
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Expand Up @@ -52,7 +52,7 @@ On a CPU-only machine:
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${PWD}/input":"/input" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-exome-case-study.md
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Expand Up @@ -68,7 +68,7 @@ curl ${HTTPDIR}/idt_capture_novogene.grch38.bed > input/idt_capture_novogene.grc
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${PWD}/input":"/input" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-hybrid-case-study.md
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Expand Up @@ -109,7 +109,7 @@ you can run this case study within about half an hour (tested on 64 CPUs).
mkdir -p output
mkdir -p output/intermediate_results_dir

BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${PWD}/input":"/input" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-ont-r104-duplex-case-study.md
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Expand Up @@ -75,7 +75,7 @@ mkdir -p "${OUTPUT_DIR}/${INTERMEDIATE_DIRECTORY}"
We will run DeepVariant from docker using the `run_deepvariant` script.

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${INPUT_DIR}":"${INPUT_DIR}" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-ont-r104-simplex-case-study.md
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Expand Up @@ -74,7 +74,7 @@ mkdir -p "${OUTPUT_DIR}/${INTERMEDIATE_DIRECTORY}"
We will run DeepVariant from docker using the `run_deepvariant` script.

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker run \
-v "${INPUT_DIR}":"${INPUT_DIR}" \
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2 changes: 1 addition & 1 deletion docs/deepvariant-pacbio-model-case-study.md
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Expand Up @@ -79,7 +79,7 @@ curl ${HTTPDIR}/HG003.GRCh38.chr20.pFDA_truthv2.bam.bai > input/HG003.GRCh38.chr

```bash
ulimit -u 10000 # https://stackoverflow.com/questions/52026652/openblas-blas-thread-init-pthread-create-resource-temporarily-unavailable/54746150#54746150
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"
mkdir -p deepvariant_output

singularity exec --bind /usr/lib/locale/ \
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4 changes: 2 additions & 2 deletions docs/deepvariant-quick-start.md
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Expand Up @@ -33,7 +33,7 @@ If you want to compile the DeepVariant binaries for yourself, we also have a
### Get Docker image

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo apt -y update
sudo apt-get -y install docker.io
Expand Down Expand Up @@ -254,7 +254,7 @@ INDEL PASS 4 4 0 13 0 9
[BAM]: http://genome.sph.umich.edu/wiki/BAM
[BWA]: https://academic.oup.com/bioinformatics/article/25/14/1754/225615/Fast-and-accurate-short-read-alignment-with
[docker build]: https://docs.docker.com/engine/reference/commandline/build/
[Dockerfile]: https://github.com/google/deepvariant/blob/r1.6/Dockerfile
[Dockerfile]: https://github.com/google/deepvariant/blob/r1.6.1/Dockerfile
[FASTA]: https://en.wikipedia.org/wiki/FASTA_format
[Quick Start in r0.7]: https://github.com/google/deepvariant/blob/r0.7/docs/deepvariant-quick-start.md
[VCF]: https://samtools.github.io/hts-specs/VCFv4.3.pdf
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12 changes: 6 additions & 6 deletions docs/deepvariant-training-case-study.md
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Expand Up @@ -62,7 +62,7 @@ YOUR_PROJECT=REPLACE_WITH_YOUR_PROJECT
OUTPUT_GCS_BUCKET=REPLACE_WITH_YOUR_GCS_BUCKET

BUCKET="gs://deepvariant"
VERSION="1.6.0"
VERSION="1.6.1"
DOCKER_IMAGE="google/deepvariant:${VERSION}"

MODEL_BUCKET="${BUCKET}/models/DeepVariant/${VERSION}/DeepVariant-inception_v3-${VERSION}+data-wgs_standard"
Expand Down Expand Up @@ -115,7 +115,7 @@ gsutil -m cp -r "${DATA_BUCKET}/HG001_GRCh37_GIAB_highconf_CG-IllFB-IllGATKHC-Io
```bash
sudo apt -y update
sudo apt -y install parallel
curl -O https://raw.githubusercontent.com/google/deepvariant/r1.6/scripts/install_nvidia_docker.sh
curl -O https://raw.githubusercontent.com/google/deepvariant/r1.6.1/scripts/install_nvidia_docker.sh
bash -x install_nvidia_docker.sh
```

Expand Down Expand Up @@ -187,7 +187,7 @@ cat "${OUTPUT_DIR}/training_set.with_label.tfrecord-00000-of-00016.gz.example_in

```json
{
"version": "1.6.0",
"version": "1.6.1",
"shape": [100, 221, 7],
"channels": [1, 2, 3, 4, 5, 6, 19]
}
Expand Down Expand Up @@ -280,7 +280,7 @@ Then, get the script that performs shuffling:

```bash
mkdir -p ${SHUFFLE_SCRIPT_DIR}
wget https://raw.githubusercontent.com/google/deepvariant/r1.6/tools/shuffle_tfrecords_beam.py -O ${SHUFFLE_SCRIPT_DIR}/shuffle_tfrecords_beam.py
wget https://raw.githubusercontent.com/google/deepvariant/r1.6.1/tools/shuffle_tfrecords_beam.py -O ${SHUFFLE_SCRIPT_DIR}/shuffle_tfrecords_beam.py
```

Next, we shuffle the data using DataflowRunner. Before that, please make sure
Expand Down Expand Up @@ -389,7 +389,7 @@ training parameters. Parameters within this training file can be overridden when
we run `train` by passing `--config.<param>=<value>`.

```bash
curl https://raw.githubusercontent.com/google/deepvariant/r1.6/deepvariant/dv_config.py > dv_config.py
curl https://raw.githubusercontent.com/google/deepvariant/r1.6.1/deepvariant/dv_config.py > dv_config.py
```

### Start `train`
Expand All @@ -406,7 +406,7 @@ this dataset, and are not recommended as the best default either.
--config=dv_config.py:base \
--config.train_dataset_pbtxt="${OUTPUT_BUCKET}/training_set.dataset_config.pbtxt" \
--config.tune_dataset_pbtxt="${OUTPUT_DIR}/validation_set.dataset_config.pbtxt" \
--config.init_checkpoint=gs://deepvariant/models/DeepVariant/1.6.0/checkpoints/wgs/deepvariant.wgs.ckpt \
--config.init_checkpoint=gs://deepvariant/models/DeepVariant/1.6.1/checkpoints/wgs/deepvariant.wgs.ckpt \
--config.num_epochs=10 \
--config.learning_rate=0.0001 \
--config.num_validation_examples=0 \
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4 changes: 2 additions & 2 deletions docs/deepvariant-vg-case-study.md
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Expand Up @@ -181,7 +181,7 @@ And then, run DeepVariant.
[DeepVariant Case Study](deepvariant-case-study.md).)

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker pull google/deepvariant:"${BIN_VERSION}"

Expand Down Expand Up @@ -253,7 +253,7 @@ INDEL PASS 504501 502199 2302 960061 1526 434935
| SNP | 3316515 | 10981 | 5550 | 0.9967 | 0.99833 | 0.997514 |

This can be compared with
https://github.com/google/deepvariant/blob/r1.6/docs/metrics.md#accuracy.
https://github.com/google/deepvariant/blob/r1.6.1/docs/metrics.md#accuracy.

Which shows that `vg giraffe` improves F1:

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2 changes: 1 addition & 1 deletion docs/deepvariant-xy-calling-case-study.md
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Expand Up @@ -72,7 +72,7 @@ mkdir -p "${OUTPUT_DIR}/${INTERMEDIATE_DIRECTORY}"
We will run DeepVariant from docker using the `run_deepvariant` script.

```bash
BIN_VERSION="1.6.0"
BIN_VERSION="1.6.1"

sudo docker pull google/deepvariant:"${BIN_VERSION}"

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2 changes: 1 addition & 1 deletion docs/runtime-by-region.md
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Expand Up @@ -47,7 +47,7 @@ make_examples runtime by region data. Continuing from the quick start, it looks
like this:

```bash
BIN_VERSION="1.6.0" # Only available in v1.1+.
BIN_VERSION="1.6.1" # Only available in v1.1+.
docker run \
-v "INPUT_DIR":"/input" \
-v "OUTPUT_DIR:/output" \
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2 changes: 1 addition & 1 deletion docs/show-examples.md
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Expand Up @@ -48,7 +48,7 @@ Once you have a make_examples output tfrecord file, then you can run
INPUT_DIR="${PWD}/quickstart-testdata"
OUTPUT_DIR="${PWD}/quickstart-output"

BIN_VERSION="1.6.0" # show_examples is available only in version 1.0.0 and later.
BIN_VERSION="1.6.1" # show_examples is available only in version 1.0.0 and later.
sudo docker run \
-v "${INPUT_DIR}":"/input" \
-v "${OUTPUT_DIR}":"/output" \
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2 changes: 1 addition & 1 deletion docs/trio-merge-case-study.md
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Expand Up @@ -115,7 +115,7 @@ serially is not the most effective approach.
```
N_SHARDS=$(nproc) # Or change to the number of cores you want to use
CAPTURE_BED=agilent_sureselect_human_all_exon_v5_b37_targets.bed
VERSION=1.6.0
VERSION=1.6.1
declare -a trio=(HG002 HG003 HG004)
for SAMPLE in "${trio[@]}"
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