Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
Enter gene symbol:

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GROUP CONDITION SAMPLES
Whole Blood
GSM3137414 GSM3137423 GSM3137426 GSM3137430 GSM3137432 GSM3137434 GSM3137439 GSM3137449 GSM3137451 GSM3137462 GSM3137465 GSM3137467 GSM3137479 GSM3137487 GSM3137489 GSM3137518 GSM3137532 GSM3137536 GSM3137540 GSM3137542 GSM3137544 GSM3137549 GSM3137553 GSM3137558 GSM3137560 GSM3137567 GSM3137568 GSM3137577 GSM3137584 GSM3137585 GSM3137590 GSM3137610 GSM3137613 GSM3137617 GSM3137618 GSM3137623 GSM3137624 GSM3137635 GSM3137638 GSM3137641 GSM3137645 GSM3137648 GSM3137651 GSM3137652 GSM3137655 GSM3137660
GSM3137416 GSM3137422 GSM3137427 GSM3137428 GSM3137443 GSM3137452 GSM3137453 GSM3137458 GSM3137472 GSM3137481 GSM3137485 GSM3137488 GSM3137493 GSM3137495 GSM3137496 GSM3137499 GSM3137513 GSM3137514 GSM3137515 GSM3137522 GSM3137523 GSM3137525 GSM3137526 GSM3137527 GSM3137534 GSM3137537 GSM3137538 GSM3137547 GSM3137556 GSM3137559 GSM3137562 GSM3137565 GSM3137566 GSM3137571 GSM3137580 GSM3137591 GSM3137594 GSM3137595 GSM3137597 GSM3137598 GSM3137608 GSM3137612 GSM3137615 GSM3137621 GSM3137628 GSM3137631 GSM3137633 GSM3137642 GSM3137643 GSM3137653 GSM3137656 GSM3137659
GSM3137413 GSM3137417 GSM3137418 GSM3137420 GSM3137421 GSM3137431 GSM3137436 GSM3137438 GSM3137442 GSM3137450 GSM3137455 GSM3137460 GSM3137463 GSM3137464 GSM3137466 GSM3137468 GSM3137471 GSM3137474 GSM3137483 GSM3137491 GSM3137497 GSM3137498 GSM3137501 GSM3137507 GSM3137509 GSM3137511 GSM3137517 GSM3137520 GSM3137521 GSM3137524 GSM3137528 GSM3137530 GSM3137531 GSM3137535 GSM3137541 GSM3137543 GSM3137545 GSM3137554 GSM3137555 GSM3137573 GSM3137574 GSM3137578 GSM3137582 GSM3137583 GSM3137589 GSM3137592 GSM3137600 GSM3137602 GSM3137604 GSM3137606 GSM3137607 GSM3137611 GSM3137616 GSM3137620 GSM3137625 GSM3137627 GSM3137630 GSM3137632 GSM3137634 GSM3137649 GSM3137661
GSM3137415 GSM3137419 GSM3137424 GSM3137425 GSM3137429 GSM3137435 GSM3137437 GSM3137441 GSM3137444 GSM3137445 GSM3137446 GSM3137447 GSM3137457 GSM3137470 GSM3137478 GSM3137484 GSM3137490 GSM3137492 GSM3137505 GSM3137506 GSM3137510 GSM3137533 GSM3137546 GSM3137548 GSM3137552 GSM3137561 GSM3137563 GSM3137569 GSM3137575 GSM3137576 GSM3137586 GSM3137593 GSM3137596 GSM3137599 GSM3137601 GSM3137609 GSM3137614 GSM3137619 GSM3137622 GSM3137629 GSM3137637 GSM3137639 GSM3137640 GSM3137654
GSM3137433 GSM3137440 GSM3137448 GSM3137454 GSM3137456 GSM3137461 GSM3137469 GSM3137473 GSM3137475 GSM3137477 GSM3137480 GSM3137494 GSM3137502 GSM3137503 GSM3137504 GSM3137508 GSM3137512 GSM3137516 GSM3137519 GSM3137529 GSM3137539 GSM3137550 GSM3137557 GSM3137570 GSM3137579 GSM3137581 GSM3137587 GSM3137588 GSM3137603 GSM3137626 GSM3137636 GSM3137644 GSM3137646 GSM3137647 GSM3137657 GSM3137658
GSM3137459 GSM3137476 GSM3137482 GSM3137486 GSM3137500 GSM3137551 GSM3137564 GSM3137572 GSM3137605 GSM3137650
Description

Submission Date: May 08, 2018

Summary: People living with diabetes have an increased risk of developing active tuberculosis. The effects of diabetes (HbA1c ≥6.5%) and intermediate hyperglycaemia (HbA1c 5.7-6.5%), on this transcriptomic signature were investigated by RNA-seq, to enhance understanding of immunological susceptibility in diabetes-tuberculosis comorbidity.Diabetes increased the magnitude of gene expression change in the host transcriptome in tuberculosis, characterised by an increase in innate, and decrease in adaptive immune responses. Strikingly, patients with intermediate hyperglycaemia and tuberculosis exhibited blood transcriptomes much more similar to diabetes-tuberculosis patients than to uncomplicated tuberculosis patients. Aberrant transcriptomes unveil a susceptibility mechanism of DM patients to TB of enhanced inflammation and reduced interferon responses.

GEO Accession ID: GSE114192

PMID: 32533832

Description

Submission Date: May 08, 2018

Summary: People living with diabetes have an increased risk of developing active tuberculosis. The effects of diabetes (HbA1c ≥6.5%) and intermediate hyperglycaemia (HbA1c 5.7-6.5%), on this transcriptomic signature were investigated by RNA-seq, to enhance understanding of immunological susceptibility in diabetes-tuberculosis comorbidity.Diabetes increased the magnitude of gene expression change in the host transcriptome in tuberculosis, characterised by an increase in innate, and decrease in adaptive immune responses. Strikingly, patients with intermediate hyperglycaemia and tuberculosis exhibited blood transcriptomes much more similar to diabetes-tuberculosis patients than to uncomplicated tuberculosis patients. Aberrant transcriptomes unveil a susceptibility mechanism of DM patients to TB of enhanced inflammation and reduced interferon responses.

GEO Accession ID: GSE114192

PMID: 32533832

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

Signatures:

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Control Condition

Perturbation Condition

Only conditions with at least 1 replicate are available to select

Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
Select differential expression analysis method:
Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.