29:null 2a:["$","title",null,{"children":"23andme V5/V4 Manifest: | lorenasandoval88 | Observable"}] 2f:Tc73,

index.js selects valid files and counts markerId | chromosome | position.
summary.js collapses markers to unique chromosome:position coordinates.
MIN_PRESENCE = 1.00 retains only coordinates found in all 20/20 files.

Metric	v4	v5
Coordinates before filtering	612,307	654,063
Coordinates present in all 20 files	596,198	622,461
23andMe `i`-probe IDs	43,796	13,929

Key result: v5 contains 26,263 more consistently observed coordinates than v4 (622,461 vs. 596,198).

These manifests are used to measure PGS Catalog model overlap with 23andMe v4 and v5 and identify models suitable for direct browser-based PRS calculation.

v5 Imputation QC: A separate imputation cohort of 63 v5 samples contained 614,637 merged sites. Filtering to biallelic SNPs with ≥90% call rate (≥57/63 samples) retained 487,366 SNPs and removed 127,271 sites. These values reflect genotype-level QC and are therefore distinct from the 622,461 marker coordinates in the 20-file v5 manifest. View imputation workflow .

30:T2079,--- # 23andMe Marker-Count Pipeline # `index.js` ## Purpose - `index.js` reads consolidated participant metadata from Google Cloud Storage. - It builds a marker-count JSON for a requested: - 23andMe chip version. - Genome build. - It: - Filters participant metadata records. - Selects matching genotype `.txt` files. - Downloads each selected file from GCS. - Parses dbSNP `rs...` IDs. - Parses 23andMe internal `i...` IDs. - Counts each exact marker record at most once per file. - Calculates marker presence across successfully processed files. - Writes the complete marker-count result to GCS. ## Required environment variables ```bash export BUCKET_NAME="all23_0710" export INPUT_METADATA_JSON="updatedParticipantsList/participants_1020_consolidated_with_build_07102026_2053.json" ``` ## Optional environment variables - `CHIP_VERSION` - Default: `v4` - Allowed values: - `v4` - `v5` - Selects the requested 23andMe chip version. - `GENOME_BUILD` - Default: `37` - Allowed values: - `37` - `38` - Selects the requested genome build. - `REQUIRE_VALID_23_FILE` - Default: `true` - When enabled, requires: ```text valid23File === true ``` - `REQUIRE_23ANDME_TYPE` - Default: `true` - When enabled: - `dataType` must exist. - `dataType` must contain `23andMe`. - `ONE_FILE_PER_PARTICIPANT` - Default: `true` - Keeps one matching file per: - Participant. - Chip version. - Genome build. - `FILE_LIMIT` - Default: `0` - Limits the number of selected files. - `0` means all matching files. - `OUTPUT_JSON` - Default: ```text marker_counts__build.json ``` - Defines the GCS output path. ## File-selection rules - By default, a file must: - Have `valid23File === true`. - Have a nonmissing `dataType`. - Have a `dataType` containing `23andMe`. - Match the requested genome build from the consolidated metadata JSON. - Have a GCS object path ending in `.txt`. - Contain exactly `_v4_Full` or `_v5_Full` in the filename. - Match the requested chip version. ## Filename classification - Accepted V4 example: ```text genome_person_v4_Full_20180705194728.txt ``` - Accepted V5 example: ```text genome_person_v5_Full_20260429131650.txt ``` - Rejected filenames include: - Filenames containing `combined`. - Filenames containing multiple chip-version tokens. - Filenames without exactly one `_v4_Full` or `_v5_Full` pattern. - Filenames with ambiguous version patterns. ## Rejected multi-version examples ```text genome_person_v3_v4_Full.txt genome_person_v4_v5_Full.txt genome_person_v3_v4_v5_Full.txt genome_person_combined_v5_Full.txt ``` ## Metadata extraction - The script searches for participants in: - A top-level array. - `participants`. - `records`. - `items`. - `data`. - `results`. - Participant IDs may be obtained from: - `id`. - `participantId`. - `userId`. - `huid`. - File paths may be obtained from: - `gcsPath`. - `gcs_path`. - `objectName`. - `path`. - The script checks both: - The main file record. - Records in `genomeBuildFiles`. ## Genome-build handling - Genome build is taken from the consolidated JSON. - The genotype file contents are not inspected to determine the build. - Recognized build-37 labels include: ```text 37 GRCh37 hg19 build 37 assembly 37 ``` - Recognized build-38 labels include: ```text 38 GRCh38 hg38 build 38 assembly 38 ``` ## Deduplication - The script sorts matching candidates by: - Newest `publishedDate`. - GCS object name when dates tie. - It removes duplicate GCS objects using: ```text bucketName/objectName ``` - When `ONE_FILE_PER_PARTICIPANT=true`, it keeps one file for each: ```text participantId | chipVersion | genomeBuild ``` - Additional matching files from the same participant are excluded with: ```text additional_file_for_same_participant ``` - `FILE_LIMIT` is applied after: - Metadata filtering. - Duplicate-object removal. - Participant deduplication. ## Chromosome normalization - Accepted chromosomes are: ```text 1-22 X Y XY MT ``` - The following labels are converted to `MT`: ```text M MTR MITO ``` - Invalid chromosome values return `null`. - Rows containing invalid chromosomes are skipped. ## Marker-ID handling - Accepted marker IDs match: ```text rs followed by digits i followed by digits ``` - Examples: ```text rs12345 i4000013 ``` - Other marker-ID formats are skipped. ## Marker-row parsing - Each non-comment row must contain at least: ```text markerId chromosome position ``` - Comment rows beginning with `#` are skipped. - Rows are skipped when: - The marker ID is invalid. - The chromosome is invalid. - The position is not a positive integer. - Fewer than three tab-delimited fields are present. ## Per-file marker deduplication - Inside each genotype file, records are keyed by: ```text markerId | chromosome | position ``` - This ensures that the same exact marker record is counted no more than once in one file. ## Aggregate count meaning - For every exact marker record: ```text fileCount = number of successfully processed files containing the exact markerId/chromosome/position combination ``` - Example: ```json { "markerId": "rs12345", "chromosome": "1", "position": 123456, "fileCount": 18, "presenceRate": 0.9, "presencePercent": 90 } ``` - If 20 files were processed successfully: ```text fileCount = 18 ``` means the exact marker record appeared in 18 of the 20 successful files. ## Presence calculations ```text presenceRate = fileCount / successfulFileCount ``` ```text presencePercent = presenceRate × 100 ``` - `presenceRate` is rounded to six decimal places. - `presencePercent` is rounded to three decimal places. ## Identifier behavior - `index.js` treats different marker IDs at the same coordinate as different records. - Example: ```text i3002758 | 18 | 29172937 rs28933979 | 18 | 29172937 ``` - These records are counted separately even though they share: ```text 18:29172937 ``` - This preserves: - dbSNP rsIDs. - 23andMe internal IDs. - Coordinate-level collapsing is performed later by `summary.js`. ## Selected-file processing - For each selected file, the script: - Downloads the GCS object. - Converts it to UTF-8 text. - Parses valid marker rows. - Builds a per-file marker map. - Adds one count for each marker in that file. - Increments `successfulFileCount`. - If a file fails: - The error is added to `failures`. - Processing continues with the remaining files. - If all files fail: - The job exits with an error. ## Main output fields - `generatedAt` - Timestamp when the output was created. - `bucketName` - GCS bucket containing the data. - `inputMetadataJson` - Metadata JSON used to select files. - `selection` - Records the active selection settings. - `metadataParticipantCount` - Number of participants in the metadata JSON. - `metadataCandidateCount` - Number of candidate file records extracted from metadata. - `selectedFileCount` - Number of files selected before processing. - `successfulFileCount` - Number of selected files processed successfully. - `failedFileCount` - Number of selected files that failed. - `excludedMetadataRecordCount` - Number of metadata records excluded during filtering. - `uniqueMarkerCoordinateCount` - Number of unique exact marker-ID and coordinate records. - `uniqueRsidCoordinateCount` - Number of records whose marker ID begins with `rs`. - `uniqueInternalIdCoordinateCount` - Number of records whose marker ID begins with `i`. - `selectedInputFiles` - Information about the selected genotype files. - `failures` - Information about files that failed to process. - `markers` - Complete marker-count array. ## Example V5 run with 20 files ```bash export BUCKET_NAME="all23_0710" export INPUT_METADATA_JSON="updatedParticipantsList/participants_1020_consolidated_with_build_07102026_2053.json" export CHIP_VERSION="v5" export GENOME_BUILD="37" export REQUIRE_VALID_23_FILE="true" export REQUIRE_23ANDME_TYPE="true" export ONE_FILE_PER_PARTICIPANT="true" export FILE_LIMIT="20" export OUTPUT_JSON="runReports/v5_20files/marker_counts_v5_build37.json" node index.js ``` ---31:T1b6c,# `summary.js` ## Purpose - `summary.js` reads the marker-count JSON produced by `index.js`. - It creates a coordinate-level summary. - It: - Downloads the marker-count JSON from GCS. - Groups records by chromosome and position. - Selects one representative marker per coordinate. - Calculates the minimum required file count. - Applies the configured presence threshold. - Sorts the retained coordinates. - Writes the summary JSON to GCS. ## Required environment variable ```bash export BUCKET_NAME="all23_0710" ``` ## Optional environment variables - `INPUT_JSON` - Default: ```text runReports/marker_counts_v5_build37.json ``` - Defines the marker-count JSON created by `index.js`. - `OUTPUT_JSON` - Default: ```text runReports/marker_counts_v5_build37_100pct.json ``` - Defines the coordinate-summary output path. - `MIN_PRESENCE` - Default: ```text 1 ``` - Accepts a value from `0` to `1`. - Defines the required fraction of successful files containing the coordinate. ## Input requirements - The input JSON must contain: ```text successfulFileCount markers ``` - `successfulFileCount` must be: - An integer. - Greater than zero. - `markers` must be an array. ## Coordinate collapsing - Records are grouped by: ```text chromosome:position ``` - Example: ```text 18:29172937 ``` - This prevents multiple marker IDs at the same physical coordinate from remaining as separate coordinate entries. ## Representative-marker rules - When multiple marker IDs occur at the same coordinate: - Keep the record with the highest `fileCount`. - If `fileCount` ties: - Prefer an `rs...` ID over an `i...` ID. - If both IDs are the same type: - Keep the marker ID that sorts first numerically. - Do not add the `fileCount` values. ## Why counts are not added - The same genotype file may contain both IDs at the same coordinate. - Adding counts could count one file more than once. - Example: ```text i3002758 at 18:29172937: fileCount = 20 rs28933979 at 18:29172937: fileCount = 7 ``` - The representative coordinate uses: ```text fileCount = 20 ``` - It does not use: ```text 20 + 7 = 27 ``` ## Representative-selection logic - If the candidate has a larger `fileCount`: ```text candidate replaces current ``` - If the counts tie and the candidate is an rsID while the current marker is not: ```text candidate replaces current ``` - If counts and ID types tie: ```text the numerically earlier marker ID is retained ``` ## Minimum file count - The threshold is converted into a whole-number file requirement using: ```js const minimumFileCount = Math.ceil( successfulFileCount * MIN_PRESENCE ); ``` - `Math.ceil()` rounds upward. - This prevents coordinates below the requested threshold from passing. ## Threshold examples for 20 successful files ### 100% threshold ```text successfulFileCount = 20 MIN_PRESENCE = 1 20 × 1 = 20 minimumFileCount = 20 ``` - A coordinate must appear in all 20 files. ### 95% threshold ```text successfulFileCount = 20 MIN_PRESENCE = 0.95 20 × 0.95 = 19 minimumFileCount = 19 ``` - A coordinate must appear in at least 19 files. ### 80% threshold ```text successfulFileCount = 20 MIN_PRESENCE = 0.8 20 × 0.8 = 16 minimumFileCount = 16 ``` - A coordinate must appear in at least 16 files. ## Inclusion rule ```text representative fileCount >= minimumFileCount ``` ## Presence values after coordinate collapsing - For each retained representative marker: ```text presenceRate = representative fileCount / successfulFileCount ``` ```text presencePercent = presenceRate × 100 ``` ## Output sorting - Retained markers are sorted by: - Chromosome. - Position. - Marker ID. - Chromosome order is: ```text 1-22 X Y XY MT ``` ## Main output fields - `generatedAt` - Timestamp when the summary was generated. - `source` - Full GCS path to the input marker-count JSON. - `successfulFileCount` - Number of files successfully processed by `index.js`. - `minimumPresence` - Presence threshold used by `summary.js`. - `minimumFileCount` - Minimum whole-number file count required to pass. - `uniqueCoordinateCountBeforeFilter` - Number of unique chromosome-position coordinates before threshold filtering. - `coordinateCountAtOrAboveThreshold` - Number of coordinates retained after threshold filtering. - `markers` - Filtered representative-marker records. ## Output marker fields ```text markerId chromosome position fileCount presenceRate presencePercent ``` ## Example retained marker ```json { "markerId": "rs12345", "chromosome": "1", "position": 123456, "fileCount": 20, "presenceRate": 1, "presencePercent": 100 } ``` ## Example V5 100% summary ```bash export BUCKET_NAME="all23_0710" export INPUT_JSON="runReports/v5_20files/marker_counts_v5_build37.json" export OUTPUT_JSON="runReports/v5_20files/marker_counts_v5_build37_100pct.json" export MIN_PRESENCE="1" node summary.js ``` ## Example V5 95% summary ```bash export BUCKET_NAME="all23_0710" export INPUT_JSON="runReports/v5_20files/marker_counts_v5_build37.json" export OUTPUT_JSON="runReports/v5_20files/marker_counts_v5_build37_95pct.json" export MIN_PRESENCE="0.95" node summary.js ``` ## Example V5 80% summary ```bash export BUCKET_NAME="all23_0710" export INPUT_JSON="runReports/v5_20files/marker_counts_v5_build37.json" export OUTPUT_JSON="runReports/v5_20files/marker_counts_v5_build37_80pct.json" export MIN_PRESENCE="0.8" node summary.js ``` --- # Complete Workflow ```text Consolidated participant metadata JSON | v index.js | | Select valid chip/build-specific files | Parse rs and internal i markers | Count exact markerId/chromosome/position records v marker_counts__build.json | v summary.js | | Collapse records by chromosome:position | Select one representative marker | Apply MIN_PRESENCE threshold v marker_counts__build_.json ``` # Key Difference Between the Scripts ## `index.js` - Counting level: - Exact marker record. - Key: ```text markerId | chromosome | position ``` - Purpose: - Preserve identifier differences. - Count rsIDs and internal 23andMe IDs separately. ## `summary.js` - Counting level: - Physical chromosome-position coordinate. - Key: ```text chromosome:position ``` - Purpose: - Collapse multiple IDs at the same physical coordinate. - Select one representative marker. - Apply the requested cross-file presence threshold. # Important Interpretation - `index.js` answers: ```text In how many successful files did this exact marker ID at this coordinate appear? ``` - `summary.js` answers: ```text In how many successful files was this physical coordinate represented by the best available marker record? ```32:Te76,toc = { const slugify = text => text .toLowerCase() .normalize("NFKD") .replace(/[\u0300-\u036f]/g, "") .replace(/[^a-z0-9]+/g, "-") .replace(/^-|-$/g, ""); return function toc({ selector = "h1",//, h2, h3", title = "Table of Contents" } = {}) { const nav = document.createElement("nav"); nav.className = "notebook-toc"; let scheduled = false; function getAllHeaders() { const cells = [ ...document.querySelectorAll(".observablehq") ]; const headers = cells.flatMap(cell => [...cell.querySelectorAll(selector)] ); // Remove duplicates and headings inside the TOC. return [...new Set(headers)] .filter(header => !nav.contains(header)) .filter(header => header.textContent.trim()) .filter(header => header.isConnected); } function render() { scheduled = false; const headers = getAllHeaders(); const usedIds = new Set( [...document.querySelectorAll("[id]")] .filter(element => !headers.includes(element)) .map(element => element.id) ); for (const header of headers) { if (!header.id) { const base = slugify(header.textContent.trim()) || "section"; let id = base; let number = 2; while (usedIds.has(id)) { id = `${base}-${number++}`; } header.id = id; } usedIds.add(header.id); } const levels = headers.map(header => Number(header.tagName.substring(1)) ); const minimumLevel = levels.length ? 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V5/V4 Manifest:","cells":[{"id":0,"value":"# 23andme V5/V4 Manifest:\n## Building an Empirical 23andMe Marker List in Google Cloud from 20 GRCh37 23andMe files per chip version.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":196,"value":"$2f","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":168,"value":"![image.png](${await FileAttachment(\"image.png\").url()})","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":204,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":170,"value":"v5 = (await (await FileAttachment(\"v5.zip\").zip())\n .file(\"v5/marker_counts_v5_build37_100pct.json\")\n 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