こんにちは、JMP コミュニティです。
一意の識別子に基づいて、Human Protein Atlas 公開 Web サイトから生物学的情報を取得する必要があります。
これまでのところ、以下の簡単なコードを使用して、Web サイトから JSON ファイルを簡単に取得して解析できます。
Names DEfault to Here (1);
ID = "ENSG00000108691";
HTM_c = "https://www.proteinatlas.org/XXX.json";
HTM_str = Substitute (HTM_c, "XXX", ID);
request = New HTTP Request (URL (HTM_str), Method ("Get"));
temp = request << send ();
js_par = Parse JSON (temp);
JSON ドキュメントの選択した部分のみを収集しようとすると、問題が発生します (添付を参照)。
1) コマンド「js_par << Get Keys」はトップレベルのキーのみを取得し、「サブキー」は利用できないままにします。
2) コマンド「js_par << Get Values」は実際の値を返しませんが、データ「コンテナ」の形式を返します。
では、JSON ドキュメントを分解して特定のキーと値を取得できるようにするにはどうすればよいでしょうか?
ヒントがあれば大歓迎です。
ありがとう。
一番、
TS
json インポート ウィザードが必要な機能を実行するかどうかを確認します。 これを攻撃するにはいくつかの方法があります。 JSL ソリューションは次のようになります。
dt = open("z:/ENSG00000108691.json",guess("huge", stack(1)),jsonwizard(0));
0 を 1 に変更すると、ウィザード ダイアログが表示されます。
このファイルには、最良の推測による選択が含まれる 8 つのレコードがあるようです。 それが期待と一致しない場合は、GUI を使用して必要なものを手動で選択することもできますが、不要な列を削除する以上のことができるかどうかはわかりません。
(ファイル -> 開く、.json 拡張子を選択、プレビューを使用してデータを選択、開きます。)
json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (and XML) dialogs are almost identical.json (および XML) ダイアログはほぼ同じです。
実際、再フォーマットした後 (Visual Studio コードは機能しました)、stack(0) を使用して 1 行を取得する方がおそらく合理的です。 各列はその列の属性のリストです (推測です)。類義語列には 8 つの可能性があります。 プロテインクラスには 5 つの可能性があります。 最初の例で示したように行に整列すべきではありません。これは意図したものではないと思います。
要求に応じて、テーブルには区切り文字を含む文字列の代わりに式列が含まれます。
[
{
"Gene": "CCL2",
"Gene synonym": [
"GDCF-2",
"HC11",
"MCAF",
"MCP-1",
"MCP1",
"MGC9434",
"SCYA2",
"SMC-CF"
],
"Ensembl": "ENSG00000108691",
"Gene description": "C-C motif chemokine ligand 2",
"Uniprot": [
"P13500"
],
"Chromosome": "17",
"Position": "34255274-34257208",
"Protein class": [
"Cancer-related genes",
"Candidate cardiovascular disease genes",
"Human disease related genes",
"Plasma proteins",
"Predicted secreted proteins"
],
"Biological process": [
"Chemotaxis",
"Inflammatory response"
],
"Molecular function": [
"Cytokine"
],
"Disease involvement": [
"Cancer-related genes"
],
"Evidence": "Evidence at protein level",
"HPA evidence": "Evidence at protein level",
"UniProt evidence": "Evidence at protein level",
"NeXtProt evidence": "Evidence at protein level",
"RNA tissue specificity": "Tissue enhanced",
"RNA tissue distribution": "Detected in all",
"RNA tissue specificity score": null,
"RNA tissue specific nTPM": {
"urinary bladder": "726.7"
},
"RNA single cell type specificity": "Cell type enhanced",
"RNA single cell type distribution": "Detected in many",
"RNA single cell type specificity score": null,
"RNA single cell type specific nTPM": {
"Ductal cells": "2990.5",
"Exocrine glandular cells": "1242.1",
"Pancreatic endocrine cells": "1696.3",
"Secretory cells": "2061.7",
"Smooth muscle cells": "1284.8"
},
"RNA cancer specificity": "Low cancer specificity",
"RNA cancer distribution": "Detected in all",
"RNA cancer specificity score": null,
"RNA cancer specific FPKM": null,
"RNA brain regional specificity": "Low region specificity",
"RNA brain regional distribution": "Detected in all",
"RNA brain regional specificity score": null,
"RNA brain regional specific nTPM": null,
"RNA blood cell specificity": "Group enriched",
"RNA blood cell distribution": "Detected in some",
"RNA blood cell specificity score": "6",
"RNA blood cell specific nTPM": {
"classical monocyte": "7.6",
"eosinophil": "3.1"
},
"RNA blood lineage specificity": "Group enriched",
"RNA blood lineage distribution": "Detected in many",
"RNA blood lineage specificity score": "6",
"RNA blood lineage specific nTPM": {
"granulocytes": "3.1",
"monocytes": "7.6"
},
"RNA cell line specificity": "Low cancer specificity",
"RNA cell line distribution": "Detected in many",
"RNA cell line specificity score": null,
"RNA cell line specific nTPM": null,
"RNA tissue cell type enrichment": [
"Pancreas - Ductal cells"
],
"RNA mouse brain regional specificity": "Low region specificity",
"RNA mouse brain regional distribution": "Detected in some",
"RNA mouse brain regional specificity score": null,
"RNA mouse brain regional specific nTPM": null,
"RNA pig brain regional specificity": "Group enriched",
"RNA pig brain regional distribution": "Detected in all",
"RNA pig brain regional specificity score": "4",
"RNA pig brain regional specific nTPM": {
"midbrain": "13.1",
"spinal cord": "52.4"
},
"Antibody": [
"CAB013676",
"HPA019163"
],
"Reliability (IH)": "Approved",
"Reliability (Mouse Brain)": null,
"Reliability (IF)": "Approved",
"Subcellular location": [
"Golgi apparatus",
"Vesicles"
],
"Secretome location": "Secreted to blood",
"Secretome function": "Chemokine",
"CCD Protein": "NA",
"CCD Transcript": "NA",
"Blood concentration - Conc. blood IM [pg\/L]": 323000,
"Blood concentration - Conc. blood MS [pg\/L]": null,
"Blood expression cluster": null,
"Tissue expression cluster": "Cluster 7: Adipose tissue - Mixed function",
"Brain expression cluster": "Cluster 12: Non-specific - Vasculature",
"Cell line expression cluster": "Cluster 49: HMC-1 - Innate immune response",
"Single cell expression cluster": "Cluster 48: Smooth muscle cells - Signal transduction",
"Interactions": 4,
"Subcellular main location": [
"Golgi apparatus"
],
"Subcellular additional location": [
"Vesicles"
],
"Antibody RRID": {
"CAB013676": null,
"HPA019163": "AB_1846179"
},
"Pathology prognostics - Breast cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "6.43e-2"
},
"Pathology prognostics - Cervical cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "4.14e-2"
},
"Pathology prognostics - Colorectal cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "4.78e-2"
},
"Pathology prognostics - Endometrial cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "5.57e-2"
},
"Pathology prognostics - Glioma": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "2.37e-3"
},
"Pathology prognostics - Head and neck cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "8.64e-2"
},
"Pathology prognostics - Liver cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "2.78e-2"
},
"Pathology prognostics - Lung cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "7.53e-2"
},
"Pathology prognostics - Melanoma": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "2.90e-1"
},
"Pathology prognostics - Ovarian cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "1.19e-1"
},
"Pathology prognostics - Pancreatic cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "9.33e-2"
},
"Pathology prognostics - Prostate cancer": {
"prognostic type": "favorable",
"is_prognostic": false,
"p_val": "2.65e-1"
},
"Pathology prognostics - Renal cancer": {
"prognostic type": "unfavorable",
"is_prognostic": true,
"p_val": "4.51e-4"
},
"Pathology prognostics - Stomach cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "1.33e-1"
},
"Pathology prognostics - Testis cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "2.50e-2"
},
"Pathology prognostics - Thyroid cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "1.81e-1"
},
"Pathology prognostics - Urothelial cancer": {
"prognostic type": "unfavorable",
"is_prognostic": false,
"p_val": "4.92e-2"
}
}
]