|
263 | 263 | text-decoration: underline; |
264 | 264 | } |
265 | 265 |
|
| 266 | + /* Examples tab styles */ |
| 267 | + .examples-container { |
| 268 | + max-width: 800px; |
| 269 | + margin: 0 auto; |
| 270 | + } |
| 271 | + |
| 272 | + .example-card { |
| 273 | + background-color: #f8f9fa; |
| 274 | + border-radius: 8px; |
| 275 | + padding: 20px; |
| 276 | + margin-bottom: 20px; |
| 277 | + box-shadow: 0 2px 4px rgba(0,0,0,0.05); |
| 278 | + } |
| 279 | + |
| 280 | + .example-title { |
| 281 | + font-size: 20px; |
| 282 | + font-weight: 600; |
| 283 | + margin-bottom: 15px; |
| 284 | + color: #333; |
| 285 | + } |
| 286 | + |
| 287 | + .example-description { |
| 288 | + margin-bottom: 15px; |
| 289 | + color: #555; |
| 290 | + line-height: 1.5; |
| 291 | + } |
| 292 | + |
| 293 | + .example-links { |
| 294 | + display: flex; |
| 295 | + gap: 15px; |
| 296 | + } |
| 297 | + |
| 298 | + .example-link { |
| 299 | + display: inline-block; |
| 300 | + padding: 8px 16px; |
| 301 | + background-color: #007bff; |
| 302 | + color: white; |
| 303 | + text-decoration: none; |
| 304 | + border-radius: 4px; |
| 305 | + font-size: 14px; |
| 306 | + transition: background-color 0.3s; |
| 307 | + } |
| 308 | + |
| 309 | + .example-link:hover { |
| 310 | + background-color: #0056b3; |
| 311 | + } |
| 312 | + |
266 | 313 | .faq-section { |
267 | 314 | padding: 20px; |
268 | 315 | max-width: 800px; |
|
535 | 582 | <div class="tabs"> |
536 | 583 | <button class="tab-button active" onclick="switchTab('home')">Home</button> |
537 | 584 | <button class="tab-button" onclick="switchTab('tab1')">Gene Set Annotation</button> |
| 585 | + <button class="tab-button" onclick="switchTab('Examples')">Examples</button> |
538 | 586 | <button class="tab-button" onclick="switchTab('tab2')">FAQ</button> |
539 | 587 | </div> |
540 | 588 |
|
@@ -629,6 +677,61 @@ <h3>Publication:</h3> |
629 | 677 | <div id="geneSetResults"></div> |
630 | 678 | </div> |
631 | 679 |
|
| 680 | + <!-- Examples Tab (New) --> |
| 681 | + <div id="Examples" class="tab-content"> |
| 682 | + <div class="examples-container"> |
| 683 | + <h2>Example Results Comparison</h2> |
| 684 | + <p class="tab-description"> |
| 685 | + Compare the results of traditional Over-Representation Analysis (ORA) with our Immune Cell Knowledge Graph (ICKG) approach on several gene sets. |
| 686 | + Click on the links to view detailed results for each example. |
| 687 | + </p> |
| 688 | + |
| 689 | + <div class="example-card"> |
| 690 | + <h3 class="example-title">CD4 Unassigned Gene Set</h3> |
| 691 | + <p class="example-description"> |
| 692 | + This example shows the pathway analysis results for CD4 T cell unassigned gene set. ICKG results provide more cell type specific and literature-backed pathway associations compared to traditional ORA. |
| 693 | + </p> |
| 694 | + <div class="example-links"> |
| 695 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD4_un1_ora.csv" class="example-link">ORA Results</a> |
| 696 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD4_un1.csv" class="example-link">ICKG Results</a> |
| 697 | + </div> |
| 698 | + </div> |
| 699 | + |
| 700 | + <div class="example-card"> |
| 701 | + <h3 class="example-title">CD4 Dysfunction Gene Set</h3> |
| 702 | + <p class="example-description"> |
| 703 | + Analysis of genes associated with CD4 T cell dysfunction. The ICKG approach reveals functional relationships backed by literature evidence, highlighting immune checkpoint pathways and exhaustion markers. |
| 704 | + </p> |
| 705 | + <div class="example-links"> |
| 706 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD4_dys_ora.csv" class="example-link">ORA Results</a> |
| 707 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD4_dys.csv" class="example-link">ICKG Results</a> |
| 708 | + </div> |
| 709 | + </div> |
| 710 | + |
| 711 | + <div class="example-card"> |
| 712 | + <h3 class="example-title">CD8 Unassigned Gene Set</h3> |
| 713 | + <p class="example-description"> |
| 714 | + Pathway analysis for CD8 T cell unassigned gene set, demonstrating how ICKG can identify relevant biological pathways that may be missed by traditional ORA approaches. |
| 715 | + </p> |
| 716 | + <div class="example-links"> |
| 717 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD8_un1_ora.csv" class="example-link">ORA Results</a> |
| 718 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD8_un1.csv" class="example-link">ICKG Results</a> |
| 719 | + </div> |
| 720 | + </div> |
| 721 | + |
| 722 | + <div class="example-card"> |
| 723 | + <h3 class="example-title">CD8 Chromatin Gene Set</h3> |
| 724 | + <p class="example-description"> |
| 725 | + This example shows analysis of chromatin-associated genes in CD8 T cells. ICKG analysis reveals specific functional relationships related to epigenetic regulation and its impact on T cell function. |
| 726 | + </p> |
| 727 | + <div class="example-links"> |
| 728 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD4_chromatin_ora.csv" class="example-link">ORA Results</a> |
| 729 | + <a href="/view-csv?file=/home/chloehe1129/immune-network/CD8_chromatin.csv" class="example-link">ICKG Results</a> |
| 730 | + </div> |
| 731 | + </div> |
| 732 | + </div> |
| 733 | + </div> |
| 734 | + |
632 | 735 | <div id="tab2" class="tab-content"> |
633 | 736 | <div class="faq-section"> |
634 | 737 | <h2 class="text-2xl font-bold mb-6">Frequently Asked Questions</h2> |
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