From 241242efde40e8c907720bc24a4f9ab2276c10d1 Mon Sep 17 00:00:00 2001 From: Miguel Covarrubias Date: Thu, 12 Oct 2023 15:38:19 -0400 Subject: [PATCH 01/13] doc updates wip --- .../variantstore/docs/aou/AOU_DELIVERABLES.md | 35 ++-- .../docs/aou/vds/delivery/Delivering a VDS.md | 162 ------------------ 2 files changed, 16 insertions(+), 181 deletions(-) delete mode 100644 scripts/variantstore/docs/aou/vds/delivery/Delivering a VDS.md diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index 98e6bbc98c4..49548bcfca5 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -2,11 +2,9 @@ ## Setup - Create a Terra workspace - - using your @pmi-ops.org account - - with the `allofus-drc-wgs-dev` Terra Billing account - - in the `AOU_DRC_WGS_OPERATORS` Authorization Domain - - Share it with `dsp-variant-team@firecloud.org` so the rest of the team can see it (Reader) and with the individual users who will be running the workflows (Owner). -- Populate the workspace with the following: + - Request a new AoU workspace per AoU DRC protocols as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). + - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. +- Once the workspace has been created and permissioned, populate with the following: - [Fetch WGS metadata for samples from list](http://app.terra.bio/#workspaces/allofus-drc-wgs-dev/GVS%20AoU%20WGS%20Charlie/notebooks/launch/Fetch%20WGS%20metadata%20for%20samples%20from%20list.ipynb) notebook - [GvsBulkIngestGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsBulkIngestGenomes) workflow - [GvsAssignIds](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsAssignIds) workflow @@ -20,11 +18,13 @@ - [GvsCallsetStatistics](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCallsetStatistics) workflow - [GvsCalculatePrecisionAndSensitivity](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCalculatePrecisionAndSensitivity) workflow - [GvsCallsetCost](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCallsetCost) workflow + - [GvsCreateVDS](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCreateVDS) workflow + - Run the "Fetch WGS metadata for samples from list" notebook after you have placed the file with the list of the new samples to ingest in a GCS location the notebook (running with your @pmi-ops account) will have access to. This will grab the samples from the workspace where they were reblocked and bring them into this callset workspace. - Set the `sample_list_file_path` variable in that notebook to the path of the file - Run the "now that the data have been copied, you can make sample sets if you wish" step if you want to automatically break up the new samples into smaller sample sets. Set the `SUBSET_SIZE` and `set_name` variables to customize. - **NOTE** If you want to create a large sample set after you have run the notebook, Terra provides (and recommends you use) this python [script](https://github.com/broadinstitute/firecloud-tools/tree/master/scripts/import_large_tsv) which allows you to upload a sample set to the workspace. -- Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name ("aou_wgs") and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). +- Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name ("aou_wgs_echo") and callset identifier (e.g. "Echo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). ## The Pipeline 1. `GvsBulkIngestGenomes` workflow @@ -53,30 +53,27 @@ - This step loads data into the `alt_allele` table from the `vet_*` tables in preparation for running the filtering step. - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. 1. `GvsCreateFilterSet` workflow - - This step calculates features from the `alt_allele` table, and trains the VQSR filtering model along with site-level QC filters and loads them into BigQuery into a series of `filter_set_*` tables. + - This step calculates features from the `alt_allele` table, and trains the VETS filtering model along with site-level QC filters and loads them into BigQuery into a series of `filter_set_*` tables. - See [naming conventions doc](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow) for guidance on what to use for `filter_set_name`, which you will need to keep track of for the `GvsExtractAvroFilesForHail` WDL. If, for some reason, this step needs to be run multiple times, be sure to use a different `filter_set_name` (the doc has guidance for this, as well). - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. 1. `GvsExtractAvroFilesForHail` workflow - - This workflow extracts the data in BigQuery and transforms it into Avro files in a Google bucket, incorporating the VQSR filter set data. - - The extracted Avro files will then be used as an input for the python script `hail_gvs_import.py` which will then be used to produce a Hail VDS. + - This workflow extracts the data in BigQuery and transforms it into Avro files in a Google bucket, incorporating the VETS filter set data. + - The extracted Avro files will then be used as an input for `GvsCreateVDS` workflow described below. - This workflow needs to be run with the `filter_set_name` from `GvsCreateFilterSet` step. - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. -1. Run the VDS Extract using a notebook terminal and the python script called `hail_gvs_import.py` from the GenerateHailScripts task in the `GvsExtractAvroFilesForHail` workflow. It will look something like: `gs://fc-/submissions//GvsExtractAvroFilesForHail//call-GenerateHailScripts/hail_gvs_import.py` - - This step creates a VDS based on the Avro files - - Notebook provisioning suggestions and other necessary set up details (e.g. the Hail wheel to use) can be found in the file: [AoU Delta VDS Cluster Configuration.md](vds/cluster/AoU%20Delta%20VDS%20Cluster%20Configuration.md) - - Avro files from the above `GvsExtractAvroFilesForHail` step can be found in the avro directory in the OutputPath task: `gs://fc-/submissions//GvsExtractAvroFilesForHail//call-OutputPath/avro` - - We suggest gsutil cp-ing `hail_gvs_import.py` to the notebook and then invoking it directly in the terminal - - inputs to the python script are: - 1. `--avro-path`: the directory path at which exported GVS Avro files are found in GCP. This path can be found by navigating to the execution directory of the `OutputPath` task in the `GvsExtractAvroFilesForHail ` workflow. The files are in a directory there named "avro". - 1. `--vds-path`: the desired output path to which the VDS should be written - 1. `--temp-path`: a convenient path to temporary directory. We suggest a folder under the GCP bucket of the workspace that the notebook is in, e.g. `gs://fc-/hail_tmp`. +1. `GvsCreateVDS` workflow + - This step creates a VDS based on the Avro files generated from the `GvsExtractAvroFilesForHail` workflow above. + - For the `avro_path` input, Avro files from the above `GvsExtractAvroFilesForHail` step can be found in the Avro directory in the `OutputPath` task: `gs://fc-/submissions//GvsExtractAvroFilesForHail//call-OutputPath/avro` + - The `vds_path` path input to this workflow represents the output path for the VDS. VDSes should be written under the AoU delivery bucket `gs://prod-drc-broad/`. Ask Lee for the exact path to use for the VDS in `#dsp-variants`. + - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. + - Once a VDS has been created the Variants team will also generate callset statistics using `GvsCallsetStatistics` as described below. The Variants team then forwards both the path to the VDS and the output callset statistics TSV to Lee to quality check the VDS. 1. `GvsPrepareRangesCallset` workflow - This workflow transforms the data in the vet tables into a schema optimized for callset stats creation and for calculating sensitivity and precision. - It will need to be run twice. Once with `only_output_vet_tables` set to "true" (the default value is `false`) and once with `control_samples` set to "true" (the default value is `false`). - See [naming conventions doc](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow) for guidance on what to use for `extract_table_prefix` or cohort prefix, which you will need to keep track of for the callset stats. Use the same prefix for both runs. - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. 1. `GvsExtractCallset` workflow - - This workflow extracts the control data in BigQuery and transforms it into a sharded joint VCF incorporating the VQSR filter set data. + - This workflow extracts the control data in BigQuery and transforms it into a sharded joint VCF incorporating the VETS filter set data. - It will need to be run once with `control_samples` set to "true", and with the `filter_set_name` from the `GvsCreateFilterSet` step and the `extract_table_prefix` from the `GvsPrepareRangesCallset` step. - Include a valid `output_gcs_dir` parameter, which is where the VCF, interval list, manifest, and sample name list files will go, e.g. `gs://fc-/extractedcontrol-vcfs/` - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. diff --git a/scripts/variantstore/docs/aou/vds/delivery/Delivering a VDS.md b/scripts/variantstore/docs/aou/vds/delivery/Delivering a VDS.md deleted file mode 100644 index 003f56667f1..00000000000 --- a/scripts/variantstore/docs/aou/vds/delivery/Delivering a VDS.md +++ /dev/null @@ -1,162 +0,0 @@ -# Delivering a VDS - -## VDS Creation and QA - -The Hail VDSes produced by GVS workflows are created within the callset workspace bucket. These are the usual -Terra workspace buckets with names like `gs://fc-secure-fb908548-fe3c-41d6-adaf-7ac20d541375`. Once a VDS has been -created the Variants team will also generate callset statistics using `GvsCallsetStatistics.wdl`. The Variants team -then forwards both the workspace path to the VDS and the output callset statistics TSV to Lee to quality check the VDS. - -## VDS Delivery to AoU - -### Have Lee determine the VDS delivery path - -Once Lee has completed his QA procedure, the Variants team can begin the process of delivering the VDS to AoU. The -designated delivery bucket for AoU callsets is `gs://prod-drc-broad/`. Within the Variants team we refer to callsets -by their [NATO phonetic alphabet](https://en.wikipedia.org/wiki/NATO_phonetic_alphabet) names (e.g. Charlie, Delta, Echo -etc.), but AoU does not use these names. - -Lee should determine what the delivery path of the VDS will be within the AoU delivery bucket. e.g. for -the Delta callset the final VDS had a workspace path -of `gs://fc-secure-fb908548-fe3c-41d6-adaf-7ac20d541375/delta_ai_an_filtered_2022_11_15.vds` and a delivery path -of `gs://prod-drc-broad/v7/wgs/without_aian_prod/vds/aou_srwgs_short_variants_v7_prod.vds`. The source path was named to -make sense to members of the Variants team, while the delivery path was completely specified by Lee, apart from the -standard delivery bucket name. - -### Collect callset workspace project info - -Both the workspace Google project id and project number are required to configure permissions for VDS delivery. The -project ID can be found in the workspace dashboard at the far left (circled in red): - -![Project number](Callset%20Workspace%20Dashboard.png) - -Using a PMI ops account and the example `terra-b3b4392d` project id we can get the project number: - -```shell -$ gcloud projects describe terra-b3b4392d --format json | jq -r .projectNumber -496370717638 -``` - -### Open PMI DRC JIRA ticket to enable STS - -At this point the Variants team needs to ask the PMI DRC to add the appropriate permissions for the STS service account -for our workspace project. This request should include our callset workspace project ID and project number we collected -in the previous step. -For reference [this](https://precisionmedicineinitiative.atlassian.net/browse/PD-8286) was the ticket used for this -purpose for the Delta callset. For Echo and other future callsets it would be necessary to do at least the second bullet -point in this ticket to add the `Storage Object Power User` role to -the `project-@storage-transfer-service.iam.gserviceaccount.com` STS service account. - -### Grant STS service account admin role on workspace bucket - -**Note:** The following steps required the use of a `@firecloud.org` account and were all performed within the Google -Cloud Console. - -For the Delta callset, I (Miguel) first went to -the [IAM page for this project](https://console.cloud.google.com/iam-admin/iam?project=terra-b3b4392d) -and granted my `mcovarr@firecloud.org` principal a `Storage Admin` role in the `terra-b3b4392d` project: - -![Firecloud Storage Admin](Firecloud%20Storage%20Admin.png) - -Once my principal had this role I could navigate to `Cloud Storage` and see the workspace bucket: - -![Workspace bucket](./Workspace%20Bucket.png) - -Clicking into the bucket, and then onto `Permissions`, I assigned the `Storage Object Admin` role to the STS service -account for the callset workspace project: - -![Service Account Permissions](./Service%20Account%20Permissions.png) - -### Perform STS transfer - -**Note:** The following steps required the use of a `@firecloud.org` account and were all performed within the Google -Cloud Console. - -**Note:** For the Delta callset the Variants -team [delivered two versions of the VDS](https://broadworkbench.atlassian.net/browse/VS-716), one with AI/AN samples and -one without. Since the text and screenshots in this document draw from both deliveries the paths and principals involved -are not consistent. Miguel's `@firecloud.org` principal was used for the version of the VDS without AI/AN and -George's `@firecloud.org` principal was used for the version with AI/AN. - -#### Go to the Storage Transfer Service (STS) Transfer Jobs Page - -From the Google Cloud Console, enter 'Storage Transfer Service' in the search bar and select the 'Data Transfer' result -(circled in red below): - -![STS Transfer Jobs Page](./STS%200.png) - -This Transfer Jobs page allows for the management of STS jobs for the project. At the top, click the 'Create Transfer -Job' "button": - -![STS Create Transfer Job](./STS%201.png) - -Clicking this button initiates a 5-step workflow. The first step is to choose the transfer job type, which for our use -case is Google Cloud Storage to Google Cloud Storage: - -![STS Get Started](./STS%202.png) - -Next choose the source path. This is a GCS URL that can be either a bucket or a directory but must not include -the `gs://` prefix. Enter the workspace path to the VDS here (remember that VDSes are directory trees): - -![STS Source](./STS%203.png) - -Now choose the destination path. Like the preceding step, this is a GCS URL that can be either a bucket or a directory -but must not include the `gs://` prefix. Enter the VDS delivery path as specified by Lee here: - -![STS Destination](./STS%204.png) - -On the next step, take the defaults of "Batch", "Run once" and "Starting now": - -![STS How and when to run](./STS%205.png) - -Finally, provide a description to identify the job, choose some conservative options, and kick off the transfer: - -* When to overwrite: Never -* When to delete: Never - -![STS Identify job](./STS%206.png) - -At this point the STS job should actually begin to run. For Delta these jobs completed in well under an hour for both -VDS deliveries. - -## Check transferred VDS - -### Configure a Terra notebook cluster - -Please follow the instructions -in [AoU Delta VDS Cluster Configuration](./AoU%20Delta%20VDS%20Cluster%20Configuration.md) to set up a Delta-scale -cluster. - -### Run Hail VDS Validation - -Hail offers -a [validate() method](https://hail.is/docs/0.2/vds/hail.vds.VariantDataset.html#hail.vds.VariantDataset.validate) on -VDS objects which "eagerly checks necessary representational properties of the VDS". This method will throw errors if -inconsistencies are found, otherwise completing without returning a result. For the Delta callset this took about an -hour or so to complete. Building on the preceding step, the following snippet validates the VDS at the delivery path: - -```python ->>> vds_path = "gs://delivery-bucket/delivery-path.vds" ->>> vds = hl.vds.read_vds(vds_path) ->>> vds.validate(); print("VDS validation successful!") -``` - -## Remove storage roles - -After the VDS has been delivered, the storage-related roles that -were [assigned above](#grant-sts-service-account-admin-role-on-workspace-bucket) to the STS service account and a -`@firecloud.org` principal should now be removed. - -### Remove admin role from STS service account - -With a `@firecloud.org` identity, navigate to the callset workspace bucket and remove the `Storage Object Admin` role -from the project's STS service account. In the dialog below, press the three trashcan icons corresponding to the three -permissions and hit `Save`: - -![Remove Storage Object Admin](./Remove%20STS%20SA%20Storage%20Object%20Admin.png) - -### Remove admin role from firecloud.org principal - -With the same `@firecloud.org` identity, navigate to IAM and remove the `Storage Admin` role from the principal: - -![Remove Storage Admin](./Remove%20Storage%20Admin.png) From 9cae3f2f3b8d5a2d5b7e8db4ff835e0bd11e86ef Mon Sep 17 00:00:00 2001 From: Miguel Covarrubias Date: Thu, 12 Oct 2023 16:04:50 -0400 Subject: [PATCH 02/13] tidy --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index 49548bcfca5..2815f34b96a 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -2,7 +2,7 @@ ## Setup - Create a Terra workspace - - Request a new AoU workspace per AoU DRC protocols as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). + - Request a new AoU workspace as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. - Once the workspace has been created and permissioned, populate with the following: - [Fetch WGS metadata for samples from list](http://app.terra.bio/#workspaces/allofus-drc-wgs-dev/GVS%20AoU%20WGS%20Charlie/notebooks/launch/Fetch%20WGS%20metadata%20for%20samples%20from%20list.ipynb) notebook From 3d9d838046ef98e1426ea5c239926e57dceb5382 Mon Sep 17 00:00:00 2001 From: Miguel Covarrubias Date: Fri, 13 Oct 2023 13:17:15 -0400 Subject: [PATCH 03/13] delete all the pictures too --- .../delivery/Callset Workspace Dashboard.png | Bin 306058 -> 0 bytes .../vds/delivery/Firecloud Storage Admin.png | Bin 260864 -> 0 bytes .../Remove STS SA Storage Object Admin.png | Bin 151826 -> 0 bytes .../aou/vds/delivery/Remove Storage Admin.png | Bin 101027 -> 0 bytes .../docs/aou/vds/delivery/STS 0.png | Bin 327264 -> 0 bytes .../docs/aou/vds/delivery/STS 1.png | Bin 136514 -> 0 bytes .../docs/aou/vds/delivery/STS 2.png | Bin 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zGiA!2{--08rL@x;xR}zsOgTpxp^~LKfKd9Vz?d55%`$~WznQmD$d?D{#R}y+!ngh) zW(YdOwLq4BB7G=D#R%>I$z#wtMU8wjBgw}rI@x^WP5lgxU2@FwrSMwFRrnlG(m55X zV&s80WdYHakaAyYnAaL&FGFs(S_(6$fo3>v@P2aP0!sm*40=pNjc4!znJ9Y^twz%+ zwA3#b&W2|J5*hk@p(H0h7=xQKygBPU8TjA(Ie2S8^!VW>Ir5Z5B$&~mlcdV3*@1F* zGL&JW$agXznlp5dnj619XhZ?+?6^(FlNmWhI Date: Mon, 16 Oct 2023 13:56:35 -0400 Subject: [PATCH 04/13] Added notebook script --- ...h WGS metadata for samples from list.ipynb | 714 ++++++++++++++++++ 1 file changed, 714 insertions(+) create mode 100644 scripts/variantstore/docs/aou/workspace/Fetch WGS metadata for samples from list.ipynb diff --git a/scripts/variantstore/docs/aou/workspace/Fetch WGS metadata for samples from list.ipynb b/scripts/variantstore/docs/aou/workspace/Fetch WGS metadata for samples from list.ipynb new file mode 100644 index 00000000000..49a69692f77 --- /dev/null +++ b/scripts/variantstore/docs/aou/workspace/Fetch WGS metadata for samples from list.ipynb @@ -0,0 +1,714 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Fetch WGS metadata for samples from list\n", + "\n", + "This notebook is intended to be run from a workspace to pull in metadata from the WGS QC workspace, given a file containing a list of samples to pull.\n", + "\n", + "Please copy this notebook into your workspace and run it there." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: toolz in /opt/conda/lib/python3.10/site-packages (0.12.0)\n", + "total 188836\n", + "-rw-rw-r-- 1 welder-user users 18391 Oct 12 19:42 'Fetch WGS metadata for samples from list.ipynb'\n", + "-rw-rw-r-- 1 welder-user users 5076 Oct 12 19:05 'Parse Delcho Sample List.ipynb'\n", + "-rw-rw-r-- 1 jupyter users 1498 Oct 12 15:55 parse_delcho_sample_tsv.py\n", + "-rw-rw-r-- 1 jupyter users 96701674 Oct 12 15:55 wgs_all_terra_delcho_v1_Oct042023_1420_10_tz0000.tsv\n", + "-rw-rw-r-- 1 jupyter users 96632331 Oct 12 16:02 wgs_pass_qc_terra_filtered_except_is_missing_from_cdr_delcho_v1_Oct042023_1420_10_tz0000.tsv\n" + ] + } + ], + "source": [ + "# uncomment and run this if you get an error importing toolz - you'll need to restart your notebook kernel after runniing this cell\n", + "!pip install toolz\n", + "!ls -l" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import json\n", + "import math\n", + "from firecloud import api as fapi\n", + "from pprint import pprint\n", + "from tqdm import tqdm\n", + "import pandas as pd\n", + "from toolz.itertoolz import partition_all" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set up source and target workspace info. You don't need to edit anything in the following cell, assuming this notebook lives in the workspace to which you'd like to copy the metadata" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "will copy data from allofus-drc-wgs-prod/AoU_DRC_WGS to allofus-drc-wgs-dev/GVS AoU Echo RD\n" + ] + } + ], + "source": [ + "# the data will be copied TO the workspace in which the notebook is run\n", + "target_ws_project = os.environ['WORKSPACE_NAMESPACE']\n", + "target_ws_name = os.environ['WORKSPACE_NAME']\n", + "target_ws_bucket = os.environ['WORKSPACE_BUCKET']\n", + "\n", + "# the data will be copied FROM the WGS QC workspace\n", + "source_ws_project = \"allofus-drc-wgs-prod\"\n", + "source_ws_name = \"AoU_DRC_WGS\"\n", + "source_ws_bucket = \"gs://fc-secure-089622a2-ae22-4dc8-ad01-634bd7634d5f\"\n", + "\n", + "print(f\"will copy data from {source_ws_project}/{source_ws_name} to {target_ws_project}/{target_ws_name}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define and fetch the file that contains the list of samples you want to fetch" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Copying gs://fc-secure-4c3976f3-d84d-4243-876f-baa9f9a4256f/wgs_pass_qc_terra_filtered_except_is_missing_from_cdr_delcho_v1_Oct042023_1420_10_tz0000.tsv...\n", + "| [1 files][ 92.2 MiB/ 92.2 MiB] \n", + "Operation completed over 1 objects/92.2 MiB. \n", + "382517\n", + "\tresearch_id\tdrc_qc_status_wgs\taw2_processing_status_wgs\tblocklist_reason_wgs\tblocklist_flag_wgs\tsample_source_wgs\tdrc_qc_status_array\taw2_processing_status_array\tblocklist_reason_array\tblocklist_flag_array\tsample_source_array\tsample_source\tsite_id\treblocked_gvcf\tsample_id\tflt_is_missing_from_cdr\tflt_is_rid_duped\tflt_suspicious_gvcf_path\tflt_suspicious_rgvcf_path\tflt_no_array_in_spot\tflt_no_array_in_terra\tflt_is_manual_blacklist\n", + "0\t1000000\t\t\t\t\t\tPASS\tPASS\t\tFALSE\tWHOLE BLOOD\tWhole Blood\tbi\tgs://prod-genomics-data-broad/ss_vcf_research/BI_A703323229_22088001176_1233191826_1.hard-filtered.gvcf.gz.reblocked.g.vcf.gz\t1000000.22088001176\tFalse\tFalse\tFalse\tFalse\tFalse\tFalse\tFalse\n", + "1\t1000004\t\t\t\t\t\tPASS\tPASS\t\tFALSE\tWHOLE BLOOD\tWhole Blood\tbi\tgs://prod-genomics-data-broad/ss_vcf_research/BI_A934715970_21092004350_0370947305_1.hard-filtered.gvcf.gz.reblocked.g.vcf.gz\t1000004.21092004350\tFalse\tFalse\tFalse\tFalse\tFalse\tFalse\tFalse\n" + ] + } + ], + "source": [ + "# EDIT THIS: localize the file containing requested samples\n", + "sample_list_file_path = \"gs://fc-secure-4c3976f3-d84d-4243-876f-baa9f9a4256f/wgs_pass_qc_terra_filtered_except_is_missing_from_cdr_delcho_v1_Oct042023_1420_10_tz0000.tsv\"\n", + "\n", + "sample_list_file = sample_list_file_path.split(\"/\")[-1]\n", + "!gsutil cp $sample_list_file_path $sample_list_file\n", + "!cat $sample_list_file | wc -l\n", + "!head $sample_list_file -n 3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Extract the list of sample_ids from your file. \n", + "NOTE: depending on how your input file was formed, you may need to do some munging to get the sample_id format - for short read WGS samples, the sample_id in Terra is composed of {research_id}.{aou_sample_id}" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "382516\n", + "['1000000.22088001176', '1000004.21092004350', '1000033.21075004006']\n" + ] + } + ], + "source": [ + "# extract just the list of samples\n", + "df_samples = pd.read_csv(sample_list_file, sep='\\t', dtype=str)\n", + "df_samples.head()\n", + "sample_list = list(df_samples['sample_id'])\n", + "\n", + "\n", + "print(len(sample_list))\n", + "print(sample_list[:3])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Perform the copy, in batches. \n", + "Feel free to edit the batch size if it helps performance." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "code_folding": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "copied 1000 samples out of 382516\n", + "copied 2000 samples out of 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382516\n", + "copied 375000 samples out of 382516\n", + "copied 376000 samples out of 382516\n", + "copied 377000 samples out of 382516\n", + "copied 378000 samples out of 382516\n", + "copied 379000 samples out of 382516\n", + "copied 380000 samples out of 382516\n", + "copied 381000 samples out of 382516\n", + "copied 382000 samples out of 382516\n", + "copied 382516 samples out of 382516\n" + ] + } + ], + "source": [ + "# copy data in batches\n", + "batch_size = 1000\n", + "total_copied = 0\n", + "\n", + "for subset_sample_list in partition_all(batch_size, sample_list): \n", + " fapi.copy_entities(source_ws_project, source_ws_name, target_ws_project, target_ws_name, \n", + " \"sample\", subset_sample_list, link_existing_entities=False)\n", + " total_copied += len(subset_sample_list)\n", + " print(f\"copied {total_copied} samples out of {len(sample_list)}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# now that the data have been copied, you can make sample sets if you wish" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# function to make new sample set\n", + "def make_new_sample_set(set_name, sample_list):\n", + " df_sample_set_table = pd.DataFrame({\"membership:sample_set_id\" : [set_name]*len(sample_list),\n", + " \"sample\" : sample_list})\n", + "\n", + " # save to tsv\n", + " sample_set_tsv = set_name + \"_sample_set_table.tsv\"\n", + " df_sample_set_table.to_csv(sample_set_tsv, sep=\"\\t\", index=False)\n", + "\n", + " # upload to Terra\n", + " response = fapi.upload_entities_tsv(target_ws_project, target_ws_name, sample_set_tsv, model=\"flexible\")\n", + " \n", + " if response.status_code != 200:\n", + " print(\"ERROR\")\n", + " print(response)\n", + " pprint(response.text)\n", + " exit(1)\n", + " else:\n", + " print(f\"successfully created new sample_set {set_name} containing {len(sample_list)} samples\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "code_folding": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "creating sample set Echo_ScaleTest...\n", + "ERROR\n", + "\n", + "('\\n'\n", + " '\\n'\n", + " '\\n'\n", + " '502 Server Error\\n'\n", + " '\\n'\n", + " '\\n'\n", + " '

      Error: Server Error

      \\n'\n", + " '

      The server encountered a temporary error and could not complete your '\n", + " 'request.

      Please try again in 30 seconds.

      \\n'\n", + " '

      \\n'\n", + " '\\n')\n" + ] + } + ], + "source": [ + "# Make one big sample set\n", + "set_name = \"Echo_ScaleTest\"\n", + "print(f\"creating sample set {set_name}...\")\n", + "make_new_sample_set(set_name, sample_list)\n", + "\n", + "# create batches of samples into sets\n", + "# SUBSET_SIZE = 50000\n", + "\n", + "\n", + "# all_set_samples = sample_list\n", + "\n", + "# subset_number = 0\n", + "\n", + "# new_subset_names = []\n", + "\n", + "# for subset_sample_list in partition_all(SUBSET_SIZE, all_set_samples): \n", + "# # name the subset\n", + "# subset_number += 1\n", + "# subset_name = f\"{set_name}_subset_{subset_number}\"\n", + "# print(f\"creating sub set {subset_name}...\")\n", + "# make_new_sample_set(subset_name, subset_sample_list)\n", + "# new_subset_names.append(subset_name)\n", + "\n", + "# print(new_subset_names)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 4999c6f43ece20e6d9755c9c3db7b5d579410666 Mon Sep 17 00:00:00 2001 From: gbggrant Date: Mon, 16 Oct 2023 13:59:42 -0400 Subject: [PATCH 05/13] Updates in AOU Deliverables doc --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index 2815f34b96a..016507b4d5a 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -4,7 +4,9 @@ - Create a Terra workspace - Request a new AoU workspace as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. -- Once the workspace has been created and permissioned, populate with the following: +- Create and push a Feature Branch (e.g. `EchoCallset`) to the ah_var_store GitHub repo + - Update the .dockstore.yml file on that feature branch to add a branch designation for all the WDLs that will be loaded into the workspace in the next step: +- Once the workspace requested above has been created and permissioned, populate with the following: - [Fetch WGS metadata for samples from list](http://app.terra.bio/#workspaces/allofus-drc-wgs-dev/GVS%20AoU%20WGS%20Charlie/notebooks/launch/Fetch%20WGS%20metadata%20for%20samples%20from%20list.ipynb) notebook - [GvsBulkIngestGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsBulkIngestGenomes) workflow - [GvsAssignIds](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsAssignIds) workflow @@ -19,12 +21,12 @@ - [GvsCalculatePrecisionAndSensitivity](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCalculatePrecisionAndSensitivity) workflow - [GvsCallsetCost](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCallsetCost) workflow - [GvsCreateVDS](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCreateVDS) workflow - -- Run the "Fetch WGS metadata for samples from list" notebook after you have placed the file with the list of the new samples to ingest in a GCS location the notebook (running with your @pmi-ops account) will have access to. This will grab the samples from the workspace where they were reblocked and bring them into this callset workspace. - - Set the `sample_list_file_path` variable in that notebook to the path of the file - - Run the "now that the data have been copied, you can make sample sets if you wish" step if you want to automatically break up the new samples into smaller sample sets. Set the `SUBSET_SIZE` and `set_name` variables to customize. +- Install and Run the steps in the [Fetch WGS metadata for samples from list](./workspace/Fetch WGS metadata for samples from list.ipynb) notebook after you have placed the file with the list of the new samples to ingest in a GCS location the notebook (running with your @pmi-ops account) will have access to. This will grab the samples from the workspace where they were reblocked and bring them into this callset workspace. + - In section 1.2, Set the `sample_list_file_path` variable in that notebook to the path of the file + - Run the cells up to and through, section 1.4 ("Perform the copy, in batches") + - If you want to automatically break up the new samples into smaller sample sets, then run the "now that the data have been copied, you can make sample sets if you wish" step. Set the `SUBSET_SIZE` and `set_name` variables to customize. - **NOTE** If you want to create a large sample set after you have run the notebook, Terra provides (and recommends you use) this python [script](https://github.com/broadinstitute/firecloud-tools/tree/master/scripts/import_large_tsv) which allows you to upload a sample set to the workspace. -- Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name ("aou_wgs_echo") and callset identifier (e.g. "Echo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). + - Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name ("aou_wgs") and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). ## The Pipeline 1. `GvsBulkIngestGenomes` workflow From 28000a9dbbb1972ece1bcbbfa78d6ce68248fbaf Mon Sep 17 00:00:00 2001 From: Rebecca Asch Date: Tue, 17 Oct 2023 10:29:37 -0400 Subject: [PATCH 06/13] added note about use_compressed_references --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index 016507b4d5a..a97b426f07f 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -32,7 +32,7 @@ 1. `GvsBulkIngestGenomes` workflow - For use with **non-control** samples only! To ingest control samples (required for running `GvsCalculatePrecisionAndSensitivity`), use the`GvsAssignIds` and `GvsImportGenomes` workflows described below. - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. - - **NOTE** Be sure to set the input `drop_state` to ZERO. This will have the effect of dropping GQ0 reference blocks. + - **NOTE** Be sure to set the input `drop_state` to ZERO (this will have the effect of dropping GQ0 reference blocks) and `use_compressed_references` to true (this will further compress the reference data). - `GvsBulkIngestGenomes` performs the functions of both `GvsAssignIds` and `GvsImportGenomes` with a much more scalable design. Detailed bulk ingest documentation can be found [here](../gvs-bulk-ingest-details.md). 1. `GvsAssignIds` workflow - For use with **control** samples only! @@ -47,6 +47,7 @@ - You will want to set the `external_sample_names`, `input_vcfs` and `input_vcf_indexes` inputs based on the columns in the workspace Data table, e.g. "this.samples.research_id", "this.samples.reblocked_gvcf_v2" and "this.samples.reblocked_gvcf_index_v2". - **NOTE** Be sure to set the input `drop_state` to ZERO. This will have the effect of dropping GQ0 reference blocks. - **NOTE** It appears that there is a rawls limit on the size of the input (list of gvcf files and indexes) per workflow run. 25K samples in a list worked for the Intermediate call set, 50K did not. + - **NOTE** Set `use_compressed_references` to true. 1. `GvsWithdrawSamples` workflow - Run if there are any samples to withdraw from the last callset. 1. **TBD Workflow to soft delete samples** From 9a7bb1a2c32fbed24504912366da95547f8ac860 Mon Sep 17 00:00:00 2001 From: Rebecca Asch Date: Tue, 17 Oct 2023 10:33:15 -0400 Subject: [PATCH 07/13] added note about use_compressed_references to GvsExtractAvroFilesForHail --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index a97b426f07f..cce0d83b062 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -64,6 +64,7 @@ - The extracted Avro files will then be used as an input for `GvsCreateVDS` workflow described below. - This workflow needs to be run with the `filter_set_name` from `GvsCreateFilterSet` step. - This workflow does not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option. + - **NOTE** Set `use_compressed_references` to true. 1. `GvsCreateVDS` workflow - This step creates a VDS based on the Avro files generated from the `GvsExtractAvroFilesForHail` workflow above. - For the `avro_path` input, Avro files from the above `GvsExtractAvroFilesForHail` step can be found in the Avro directory in the `OutputPath` task: `gs://fc-/submissions//GvsExtractAvroFilesForHail//call-OutputPath/avro` From a4731cddfe0d57406d86e02ffe5598dc52dbbdce Mon Sep 17 00:00:00 2001 From: George Grant Date: Tue, 17 Oct 2023 13:38:01 -0400 Subject: [PATCH 08/13] Update scripts/variantstore/docs/aou/AOU_DELIVERABLES.md Co-authored-by: Bec Asch --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index cce0d83b062..d8127480564 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -26,7 +26,7 @@ - Run the cells up to and through, section 1.4 ("Perform the copy, in batches") - If you want to automatically break up the new samples into smaller sample sets, then run the "now that the data have been copied, you can make sample sets if you wish" step. Set the `SUBSET_SIZE` and `set_name` variables to customize. - **NOTE** If you want to create a large sample set after you have run the notebook, Terra provides (and recommends you use) this python [script](https://github.com/broadinstitute/firecloud-tools/tree/master/scripts/import_large_tsv) which allows you to upload a sample set to the workspace. - - Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name ("aou_wgs") and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). +- Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name (e.g. "aou_wgs" — if it does not exist be sure to create one before running any workflows) and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). ## The Pipeline 1. `GvsBulkIngestGenomes` workflow From 3a3365d8a3e5b573565063cc4994c1079d0715f0 Mon Sep 17 00:00:00 2001 From: gbggrant Date: Tue, 17 Oct 2023 13:43:03 -0400 Subject: [PATCH 09/13] Updates from code review. --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index d8127480564..e095f8bfc0e 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -6,8 +6,7 @@ - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. - Create and push a Feature Branch (e.g. `EchoCallset`) to the ah_var_store GitHub repo - Update the .dockstore.yml file on that feature branch to add a branch designation for all the WDLs that will be loaded into the workspace in the next step: -- Once the workspace requested above has been created and permissioned, populate with the following: - - [Fetch WGS metadata for samples from list](http://app.terra.bio/#workspaces/allofus-drc-wgs-dev/GVS%20AoU%20WGS%20Charlie/notebooks/launch/Fetch%20WGS%20metadata%20for%20samples%20from%20list.ipynb) notebook +- Once the workspace requested above has been created and permissioned, populate with the following WDLs: - [GvsBulkIngestGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsBulkIngestGenomes) workflow - [GvsAssignIds](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsAssignIds) workflow - [GvsImportGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsImportGenomes) workflow @@ -21,10 +20,12 @@ - [GvsCalculatePrecisionAndSensitivity](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCalculatePrecisionAndSensitivity) workflow - [GvsCallsetCost](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCallsetCost) workflow - [GvsCreateVDS](https://dockstore.org/workflows/github.com/broadinstitute/gatk/GvsCreateVDS) workflow -- Install and Run the steps in the [Fetch WGS metadata for samples from list](./workspace/Fetch WGS metadata for samples from list.ipynb) notebook after you have placed the file with the list of the new samples to ingest in a GCS location the notebook (running with your @pmi-ops account) will have access to. This will grab the samples from the workspace where they were reblocked and bring them into this callset workspace. - - In section 1.2, Set the `sample_list_file_path` variable in that notebook to the path of the file - - Run the cells up to and through, section 1.4 ("Perform the copy, in batches") - - If you want to automatically break up the new samples into smaller sample sets, then run the "now that the data have been copied, you can make sample sets if you wish" step. Set the `SUBSET_SIZE` and `set_name` variables to customize. +- Install the [Fetch WGS metadata for samples from list](./workspace/Fetch%20WGS%20metadata%20for%20samples%20from%20list.ipynb) python notebook in the workspace that has been created. + - Placed the file with the list of the new samples to ingest in a GCS location the notebook (running with your @pmi-ops account) will have access to. This will grab the samples from the workspace where they were reblocked and bring them into this callset workspace. + - Run the steps in the notebook: + - In section 1.2, Set the `sample_list_file_path` variable in that notebook to the path of the file + - Run the cells up to and through, section 1.4 ("Perform the copy, in batches") + - If you want to automatically break up the new samples into smaller sample sets, then run the "now that the data have been copied, you can make sample sets if you wish" step. Set the `SUBSET_SIZE` and `set_name` variables to customize. - **NOTE** If you want to create a large sample set after you have run the notebook, Terra provides (and recommends you use) this python [script](https://github.com/broadinstitute/firecloud-tools/tree/master/scripts/import_large_tsv) which allows you to upload a sample set to the workspace. - Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name (e.g. "aou_wgs" — if it does not exist be sure to create one before running any workflows) and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). From 8ffe9e82842f238c0d96ca594f0555a338163755 Mon Sep 17 00:00:00 2001 From: gbggrant Date: Wed, 18 Oct 2023 10:56:20 -0400 Subject: [PATCH 10/13] Update documentation to mention creating the dataset as 'Multi-Region' --- scripts/variantstore/docs/DELIVERING_GVS_VCF.md | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/variantstore/docs/DELIVERING_GVS_VCF.md b/scripts/variantstore/docs/DELIVERING_GVS_VCF.md index 968042c1beb..23142d8bbed 100644 --- a/scripts/variantstore/docs/DELIVERING_GVS_VCF.md +++ b/scripts/variantstore/docs/DELIVERING_GVS_VCF.md @@ -26,6 +26,7 @@ - In-use IP addresses: 5,000 (this is the most challenging one and will probably require contacting the GCP account team to facilitate) - Concurrent connections per project for small regions per region: 2,000 - AppendRows throughput per project for small regions per minute per region: 2,000 (this is as it was written) +- Create a dataset in the Google project. Make sure that when you are creating the dataset that you set the `location type` to be `Multi-Region` - Make a note of the Google project ID, BigQuery dataset name, and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). ## The Pipeline From 355b83fd68c777b62cadafa2f2a98ab44aa6a6aa Mon Sep 17 00:00:00 2001 From: gbggrant Date: Wed, 18 Oct 2023 10:58:50 -0400 Subject: [PATCH 11/13] And put the documentation in the right place --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index e095f8bfc0e..a756f3fd517 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -27,6 +27,7 @@ - Run the cells up to and through, section 1.4 ("Perform the copy, in batches") - If you want to automatically break up the new samples into smaller sample sets, then run the "now that the data have been copied, you can make sample sets if you wish" step. Set the `SUBSET_SIZE` and `set_name` variables to customize. - **NOTE** If you want to create a large sample set after you have run the notebook, Terra provides (and recommends you use) this python [script](https://github.com/broadinstitute/firecloud-tools/tree/master/scripts/import_large_tsv) which allows you to upload a sample set to the workspace. +- Create a dataset in the Google project. Make sure that when you are creating the dataset that you set the `location type` to be `Multi-Region` - Make a note of the Google project ID ("aou-genomics-curation-prod"), dataset name (e.g. "aou_wgs" — if it does not exist be sure to create one before running any workflows) and callset identifier (e.g. "Bravo") as these will be inputs (`project_id`, `dataset_name` and `call_set_identifier`) to all or most of the GVS workflows. The [naming conventions for other aspects of GVS datasets are outlined here](https://docs.google.com/document/d/1pNtuv7uDoiOFPbwe4zx5sAGH7MyxwKqXkyrpNmBxeow). ## The Pipeline From 205f12e283e13d05ae0900f7e87cfa36706951bc Mon Sep 17 00:00:00 2001 From: George Grant Date: Tue, 24 Oct 2023 14:12:39 -0400 Subject: [PATCH 12/13] Update scripts/variantstore/docs/aou/AOU_DELIVERABLES.md Co-authored-by: Miguel Covarrubias --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index a756f3fd517..14cab75a5ec 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -4,7 +4,7 @@ - Create a Terra workspace - Request a new AoU workspace as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. -- Create and push a Feature Branch (e.g. `EchoCallset`) to the ah_var_store GitHub repo +- Create and push a feature branch (e.g. `EchoCallset`) based off the `ah_var_store` branch to the GATK GitHub repo. - Update the .dockstore.yml file on that feature branch to add a branch designation for all the WDLs that will be loaded into the workspace in the next step: - Once the workspace requested above has been created and permissioned, populate with the following WDLs: - [GvsBulkIngestGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsBulkIngestGenomes) workflow From 81aad19c3ac3d9a469aa3fa7bcfa176e4e0be0e4 Mon Sep 17 00:00:00 2001 From: George Grant Date: Tue, 24 Oct 2023 14:12:47 -0400 Subject: [PATCH 13/13] Update scripts/variantstore/docs/aou/AOU_DELIVERABLES.md Co-authored-by: Miguel Covarrubias --- scripts/variantstore/docs/aou/AOU_DELIVERABLES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md index 14cab75a5ec..a1822ec75dc 100644 --- a/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md +++ b/scripts/variantstore/docs/aou/AOU_DELIVERABLES.md @@ -5,7 +5,7 @@ - Request a new AoU workspace as described in Section 3.D. of [AoU DRC Protocols](https://docs.google.com/document/d/1ooK0wbHLgSueiepjTTyLLI6Zz7vi1-GhKTjmCd8ZHwU/edit?usp=sharing). - As described in the "Getting Started" of [Operational concerns for running Hail in Terra Cromwell/WDL](https://docs.google.com/document/d/1_OY2rKwZ-qKCDldSZrte4jRIZf4eAw2d7Jd-Asi50KE/edit?usp=sharing), this workspace will need permission in Terra to run Hail dataproc clusters within WDL. Contact Emily to request this access as part of setting up the new workspace. - Create and push a feature branch (e.g. `EchoCallset`) based off the `ah_var_store` branch to the GATK GitHub repo. - - Update the .dockstore.yml file on that feature branch to add a branch designation for all the WDLs that will be loaded into the workspace in the next step: + - Update the .dockstore.yml file on that feature branch to add the feature branch for all the WDLs that will be loaded into the workspace in the next step. - Once the workspace requested above has been created and permissioned, populate with the following WDLs: - [GvsBulkIngestGenomes](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsBulkIngestGenomes) workflow - [GvsAssignIds](https://dockstore.org/my-workflows/github.com/broadinstitute/gatk/GvsAssignIds) workflow