diff --git a/.spelling b/.spelling index 2ee7acc0..d75eb443 100644 --- a/.spelling +++ b/.spelling @@ -597,6 +597,7 @@ deconvoluting DMG-H3 gemcitabine Hematopoiesis +iDAT Illumina in-vitro in-vivo diff --git a/content/3.genomics-platform/1.getting-started/3.making-a-data-request.md b/content/3.genomics-platform/1.getting-started/3.making-a-data-request.md index 40b17b09..a674c365 100644 --- a/content/3.genomics-platform/1.getting-started/3.making-a-data-request.md +++ b/content/3.genomics-platform/1.getting-started/3.making-a-data-request.md @@ -124,3 +124,15 @@ If you receive an email from us that your DAA is incomplete, you may edit your D ## Managing your Data Request Go to our [Managing Data Overview](/genomics-platform/managing-data/overview) documentation page to learn how to check the status of your data request, complete an EDAA draft, upload a revised DAA, and ultimately access your data from your [My Dashboard](https://platform.stjude.cloud/requests/manage) page. + +## Unrestricted Data + +Certain Data within Genomics Platform is unrestricted, meaning that access is available to all requestors and does not require a data access agreement. + +To access this data, please complete the following steps: + +1. Create an account on or log in to Genomics Platform. +2. Narrow your selection by filtering to Feature Count Files only and/or iDAT files only and then selecting Request Data at the bottom right of the screen. +3. Choose to vend the data to a new or existing project +4. Submit the request. +5. The data will be vended to your selected project in a folder labeled with the date the data was requested. diff --git a/content/3.genomics-platform/2.about-our-data/1.data-sets-and-data-access-units.md b/content/3.genomics-platform/2.about-our-data/1.data-sets-and-data-access-units.md index 21713fa5..d6cd40ac 100644 --- a/content/3.genomics-platform/2.about-our-data/1.data-sets-and-data-access-units.md +++ b/content/3.genomics-platform/2.about-our-data/1.data-sets-and-data-access-units.md @@ -9,6 +9,7 @@ title: Data Sets and Data Access Units - [Data Set](#data-set) - [Data Access Committee (DAC)](#data-access-committee-dac) - [Embargo Date](#embargo-date) + - [Unrestricted Data](#unrestricted-data) - [List of DAUs](#list-of-daus) - [List of Data Sets](#list-of-data-sets) @@ -62,6 +63,16 @@ Publishing using any of the files _before_ the embargo date has passed is strict Some Data, including Data funded by the NIH, are not subject to embargo. Applicable Embargo Dates can be found in [Genomics Platform Metadata](https://platform.stjude.cloud/api/v1/manifest.tsv){target="_blank"} in the `SJ_Embargo_Date` column. +### Unrestricted Data + +Certain data within the Genomics Platform is unrestricted. Unrestricted data is not subject to DAC-reviewed approval before a user can obtain it. +The unrestricted dataset on St. Jude Cloud currently includes: + +- Feature count files +- [COMET](https://comet.stjude.org/) iDAT files + +Steps to access unrestricted data can be found [here](http://docs.stjude.cloud/genomics-platform/getting-started/making-a-data-request#unrestricted-data). + --- ## List of DAUs @@ -158,7 +169,7 @@ The following data set(s) are included within SJLIFE: ## List of Data Sets -We currently have 21 [Data Sets](#data-set) listed below. +We currently have 22 [Data Sets](#data-set) listed below. Additional information can also be seen including which [Data Access Units (DAU)](#data-access-unit-dau) the Data Set belongs to, tissue type, sequencing type, number of samples, additional links, and a brief description. | Data Set | DAU(s) | Tissue Type | Sequencing | Samples | @@ -167,6 +178,7 @@ Additional information can also be seen including which [Data Access Units (DAU) | [CCSS](#childhood-cancer-survivor-study) | CCSS | Germline Only | WGS | 2,912 | | [CICERO Benchmark](#cicero-benchmark) | PCGP, Clinical Genomics | Paired Tumor-Normal | RNA-Seq | 124 | | [Clinical Pilot](#clinical-pilot) | PCGP, Clinical Genomics | Paired Tumor-Normal | WGS, WES, RNA-Seq | 155 | +| [COMET](#comet) | Unrestricted | iDAT file | — | 4269 | | [CReATe](#clinical-research-in-als-and-related-disorders-for-therapeutic-development-consortium) | CReATe | PBMC Germline DNA | WGS | 705 | | [CSTN](#childhood-solid-tumor-network) | PCGP, Clinical Genomics | Paired Tumor-Normal | WGS, WES, RNA-Seq | 143 | | [G4K](#genome-4-kids) | PCGP, Clinical Genomics | Paired Tumor-Normal | WGS, WES, RNA-Seq | 565 | @@ -183,7 +195,7 @@ Additional information can also be seen including which [Data Access Units (DAU) | [RTCG](#real-time-clinical-genomics) | PCGP, Clinical Genomics | Paired Tumor-Normal | WGS, WES, RNA-Seq | 7,767 | | [SGP](#sickle-cell-genome-project) | SGP | Germline Only | WGS | 807 | | [SJLIFE](#st-jude-life) | SJLIFE | Germline Only | WGS, WES | 4,838 | -| [SJLIFE_ClonalHematopoiesis](#st-jude-life-clonal-hematopoiesis) | SJLIFE | — | Single Cell-WGS, Targeted | 3,192 | +| [SJLIFE_ClonalHematopoiesis](#st-jude-life-clonal-hematopoiesis) | PCGP | — | Single Cell-WGS, Targeted | 3,192 | | [tMN](#pediatric-therapy-related-myeloid-neoplasms-tmn) | PCGP | Paired Tumor-Normal | WGS, WES, RNA-Seq | 206 | ### Atypical Teratoid / Rhabdoid Tumor-derived Tumoroid Models @@ -254,6 +266,14 @@ In addition to patients enrolled in the PGB1 Cohort (primary participants), the This dataset includes WGS data from N=705 in PGB1, including N=472 ALS/ALS-FTD, N=20 PMA, N=47 PLS, N=162 HSP, and N=4 with other related disorders. The findings of the project were published in [Translational Neurodegeneration](https://translationalneurodegeneration.biomedcentral.com/articles/10.1186/s40035-025-00516-2). +### COMET + +**DAU**: - | **Tissue Type**: - | **Assay Type**: Illumina Infinium 850K array | **Samples**: 4,629| **[Additional Information About COMET](https://www.stjude.org/research/departments/computational-biology/comet.html)** + +The solid tumor COmprehensive METhylation (COMET) database is a searchable repository of pediatric solid tumor DNA methylation and copy number variant (CNV) profiles, generated using the Illumina Infinium 850K array, paired with matched whole slide histology images (WSI). +It is the largest and most comprehensive extracranial pediatric solid tumor epigenetic reference dataset in the world, offering DNA methylation profiles across 20 different types of pediatric solid tumors along with a comparative collection of patient-derived orthotopic xenografts, cell lines, adult sarcomas, and normal tissues. +See [Unrestricted Data](#unrestricted-data) for more details on requesting access to this data set. + ### DMG-H3K27a Clonal Evolution **DAU**: PCGP | **Tissue Type**: — | **Sequencing Type**: WGS, WES | **Samples**: 70 diff --git a/content/3.genomics-platform/2.about-our-data/2.file-formats-and-sequencing-information.md b/content/3.genomics-platform/2.about-our-data/2.file-formats-and-sequencing-information.md index 6f16b861..d83cff3d 100644 --- a/content/3.genomics-platform/2.about-our-data/2.file-formats-and-sequencing-information.md +++ b/content/3.genomics-platform/2.about-our-data/2.file-formats-and-sequencing-information.md @@ -13,6 +13,7 @@ St. Jude Cloud hosts both raw genomic data files and processed results files: | Somatic VCF | Curated list of somatic variants produced by the St. Jude somatic variant analysis pipeline. | [Click here](#somatic-vcf-files) | | CNV | List of somatic copy number alterations produced by St. Jude CONSERTING pipeline. | [Click here](#cnv-files) | | Feature Counts | Curated list of read counts mapped to each gene produced by [HTSeq](https://htseq.readthedocs.io/en/master/) | [Click here](#feature-counts-files) | +| iDAT | Raw, paired intensity files output by an Illumina microarray scanner for a single sample — one per fluorescence channel — before normalization or genotype/methylation calling. | [Click here](#idat-files) | ### BAM files @@ -195,6 +196,11 @@ The files are tab-delimited text and contain the feature key and read count for [rnaseq-rfc]: https://stjudecloud.github.io/rfcs/0001-rnaseq-workflow-v2.0.0.html#specification [gencode]: https://www.gencodegenes.org/human/release_31.html +### iDAT files + +These are the raw, paired intensity files output by an Illumina microarray for a single sample. +Each sample includes two IDAT files — one per fluorescence channel (Green and Red) containing the raw, unprocessed probe intensity signal from the array before any normalization or genotype/methylation calling. + ## Sequencing Information ### Whole Genome and Whole Exome diff --git a/content/4.pecan/1.overview/1.getting-started.md b/content/4.pecan/1.overview/1.getting-started.md index def358a5..879a1d6d 100644 --- a/content/4.pecan/1.overview/1.getting-started.md +++ b/content/4.pecan/1.overview/1.getting-started.md @@ -98,6 +98,16 @@ Data Facets represent a distinct type of post-processed genomic data for collect +
+
+ Epigenetics +
+
+
Epigenetics
+

Methylation landscape of over 4,400 pediatric cancer samples in PeCan.

+
+
+ ## Tools
diff --git a/content/4.pecan/2.data-facets/5.epigenetics.md b/content/4.pecan/2.data-facets/5.epigenetics.md new file mode 100644 index 00000000..431ce349 --- /dev/null +++ b/content/4.pecan/2.data-facets/5.epigenetics.md @@ -0,0 +1,87 @@ +--- +title: Epigenetics +--- + +![Epigenetics](/img/pecan/overview/getting-started/histology.svg) +Explore the methylation landscape of over 4,400 pediatric cancer samples in PeCan. + +## Overview + +The Epigenetics facet lets you explore methylation data across 4,400+ pediatric cancer samples. +Navigate the data using a UMAP plot with gene- or probe-level overlays of β-values, or view it collectively in a data table. + +## UMAP Overlay Features + +On page load, each sample on the UMAP is colored by its cancer subtype. +When you select a gene or probe to overlay, the sample color changes to a gradient representative of the β-value for the sample. +β-value is the range in which the target is methylated, with 0 being fully unmethylated and 1 being fully methylated; values can range from 0 to 1. +You can overlay either the mean or median β-value; mean is selected by default (see β-value Toggle below). + +### Gene Overlay + +Select one or more genes to overlay their associated methylation on the UMAP. +The overlay shows the mean β-value across all probes mapped to the selected gene by default. +You can toggle to the median β-value or switch between selected genes to compare. +To narrow results, apply filters to display only probes in the promoter region, specifically TSS1500 and/or TSS200. + +### Probe Overlay + +Select one or more probe IDs to overlay their methylation values on the UMAP. +The overlay shows the mean β-value for the selected probe. +The probe overlay is only available for CpG probes that start with `cg`. + +### Overlay Considerations + +The UMAP and its overlays are drawn from the same underlying dataset, but different filters are applied depending on the view. +Understanding these filtering rules helps you interpret what you see. + +### Probe Filtering by Analysis Level + +| Level | Low Quality Filter | Common SNP Probes | Cross Reactive Probes | Sex Chromosome Probes | +|---------------------|--------------------|-------------------|-----------------------|-----------------------| +| UMAP | Yes | Yes | No | Yes | +| Gene level overlay | Yes | Yes | No | No | +| Probe level overlay | Yes | No | No | No | + +### Filter Descriptions + +- **Low Quality Filter:** Removes probes that fail quality control thresholds. +- **Common SNP Probes:** Excludes probes located at common single nucleotide polymorphisms to reduce genotype-driven variation. +- **Cross Reactive Probes:** Excludes probes known to hybridize to multiple genomic locations. +Currently not applied at any level. +Please refer to the following lists of cross-reactive probes: + - Pidsley Cross-Reactive Probes + - McCartney Supplement Probes +- **Sex Chromosome Probes:** Excludes probes on the X and Y chromosomes. +Applied only at the UMAP level to prevent sex-driven clustering. + +## Data Table Features + +Select the Data tab to view a table of samples with corresponding metadata. +Columns include Sample ID, Diagnosis Subtype Code, and Diagnosis Subtype Name. +β-value columns are sortable, allowing you to rank samples by methylation level for a given gene or probe. + +## How to Narrow and Refine the Data + +- **Filters:** Filter samples by Sample ID(s), Subtype Root, Subtype, Subtype Biomarkers, Patient Phenotype (sex, age at diagnosis, race, ethnicity), or Sample Preparation parameters. +- **Lasso and Pan/Zoom:** Use the Lasso tool to select a region of samples on the UMAP, or Pan/Zoom to focus on a specific area. +- **β-value Toggle:** In the UMAP tab header, toggle between mean and median β-values for the gene overlay. +Mean is selected by default. +- **Hover and Drawer:** + - **Sample Hover:** Hover over or click a sample on the UMAP to view its metadata (diagnosis, demographics, etc.). + - **Gene Overlay Hover:** Hover over the selected gene to view probe-level data for that gene. + +## Menu Options (⋯) + +Access additional features from the three-dot menu in the header: + +- Show or hide diagnosis category labels on the UMAP +- Copy the URL for the current UMAP view +- Copy Sample IDs for the current view +- Copy data as TSV +- Export the current UMAP as SVG + +## UMAP Generation + +Methylation β-values were generated using the Infinium MethylationEPIC BeadChip v1.0 array and normalized with subset-quantile within-array normalization (SWAN) to correct for probe-type bias between Type I and Type II probes. After normalization, the standard deviation of β-values was calculated per probe, and the 10,000 probes with the highest standard deviation were kept for UMAP generation. +Probes associated with SNPs at CpG sites, cross-reactive probes, and probes on sex chromosomes were excluded. diff --git a/content/4.pecan/2.data-facets/5.use-cases.md b/content/4.pecan/2.data-facets/6.use-cases.md similarity index 100% rename from content/4.pecan/2.data-facets/5.use-cases.md rename to content/4.pecan/2.data-facets/6.use-cases.md diff --git a/deployment/preview/pr184/app.yaml b/deployment/preview/pr184/app.yaml new file mode 100644 index 00000000..66fa251e --- /dev/null +++ b/deployment/preview/pr184/app.yaml @@ -0,0 +1,87 @@ +apiVersion: helm.toolkit.fluxcd.io/v2 +kind: HelmRelease +metadata: + name: docs + namespace: docs-pr184 +spec: + interval: 30m + chart: + spec: + chart: generic + version: 1.1.x + sourceRef: + kind: HelmRepository + name: stjudecloud + namespace: flux-system + interval: 1h + values: + nameOverride: docs + extraDeploy: + - | + apiVersion: v1 + kind: Service + metadata: + name: {{ template "common.names.fullname" . }}-oauth-bridge + labels: {{- include "common.labels.standard" . | nindent 4 }} + {{- if .Values.commonLabels }} + {{- include "common.tplvalues.render" ( dict "value" .Values.commonLabels "context" $ ) | nindent 4 }} + {{- end }} + {{- if .Values.commonAnnotations }} + annotations: {{- include "common.tplvalues.render" ( dict "value" .Values.commonAnnotations "context" $ ) | nindent 4 }} + {{- end }} + spec: + type: ExternalName + externalName: oauth2-proxy.oauth2-proxy + - | + --- + apiVersion: networking.k8s.io/v1 + kind: Ingress + metadata: + name: {{ .Release.Name }}-oauth + spec: + ingressClassName: nginx + rules: + - host: {{ .Values.ingress.hostname }} + http: + paths: + - backend: + service: + name: {{ template "common.names.fullname" . }}-oauth-bridge + port: + number: 80 + path: /oauth2 + pathType: ImplementationSpecific + tls: + - hosts: + - {{ .Values.ingress.hostname }} + secretName: {{ .Values.ingress.hostname }}-tls + image: + repository: stjudecloud/docs + tag: pr184-318878b-406 # {"$imagepolicy": "flux-system:docs-pr184:tag"} + podAnnotations: + linkerd.io/inject: enabled + config.linkerd.io/proxy-cpu-request: 20m + containerPorts: + http: 3000 + service: + ports: + - name: http + protocol: TCP + port: 3000 + targetPort: http + ingress: + enabled: true + hostname: docs-pr184.staging.stjude.cloud + path: / + annotations: + cert-manager.io/cluster-issuer: letsencrypt-prod + linkerd.io/inject: ingress + nginx.ingress.kubernetes.io/auth-signin: https://$host/oauth2/start?rd=$escaped_request_uri + nginx.ingress.kubernetes.io/auth-url: https://$host/oauth2/auth + nginx.ingress.kubernetes.io/service-upstream: "true" + nginx.ingress.kubernetes.io/enable-modsecurity: "true" + nginx.ingress.kubernetes.io/enable-owasp-core-rules: "true" + tls: + enabled: true + datadog: + enabled: false