GSE177044

Large-scale whole blood RNA-Seq identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis 

Whole-study status Not suitable

Dataset does not meet the current suitability threshold.

Whole-study downloads — these do not apply your sample requirements.

Selected cohort requirements

Samples meeting selected requirements: 0 cases / 0 controls

View matching samples

Patient pairs verified in indexed sample metadata: 0

A case/control comparison meeting these requirements is not confirmed.

Counts describe samples, not independent patients. Pair verification uses explicit subject identifiers in indexed sample metadata. Zero verified pairs does not establish that the study is unpaired; reported matched-normal design alone is insufficient.

Source
GEO
Assay
bulk RNA-seq
Organism
Homo sapiens
Whole-study samples
1035 samples
Specimen
Biofluid
Reported/interpreted study design
Disease/model vs control Design classification does not establish patient pairs.
Comparison type
Tumor vs normal
Contributors
Wacker EM, Uellendahl-Werth F, Bej S, Wolkenhauer O, Vesterhus M, Lieb W, Franke A, Karlsen TH, Folseraas T, Ellinghaus D
Contact name
Florian Uellendahl-Werth
Submission date
2021-06-11
Last update
2024-02-14
Organization
Christian-Albrechts Universität zu Kiel
Department
Institute of Clinical Molecular Biology (IKMB)
Public date
2024-01-22
Experiment types
Expression profiling by high throughput sequencing
Platforms
GPL16791 Illumina HiSeq 2500 (Homo sapiens)
Series type
Series
SubSeries
Not available
BioProject
PRJNA736966

Summary

Background: Patients suffering from primary sclerosing cholangitis (PSC) often also have ulcerative colitis (UC). Cross-disease genetic and microbiome studies across PSC und UC patients indicated that UC in PSC is a separate disease entity from primary UC, but expression studies for PSC are lacking. In this study, we performed a molecular comparison of whole blood expression levels in PSC only, PSC patients with additional UC diagnosis (PSC/UC), and UC, using a large collection of whole blood transcriptome data. Methods: We conducted whole blood RNA-Seq experiments for 495 UC patients, 220 PSC patients (of whom 177 have also a UC diagnosis), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses. Results: The blood transcriptome in UC and PSC is dominated by neutrophil activation genes. In UC, but not in PSC (neither PSC alone nor PSC/UC), there is upregulation of genes for ribosomes, mitochondria and energy metabolism genes in conjunction with antibody transcript expression. In PSC, there is an increase in modules related to apoptosis and expression of genes of interferon-I-related ontologies. Random forest analysis could poorly discriminate PSC alone from PSC/UC (AUROC 0.56), but could discriminate PSC, UC, and controls with high accuracy (AUROC UC vs controls 0.95, PSC vs controls 0.88, UC vs PSC 0.986). The main coexpression modules are enriched in neutrophil degranulation and antibody production genes relevant for distinguishing PSC, UC, and controls. Conclusions: PSC and UC share neutrophil-related transcriptional upregulation in whole blood (e.g. S100A12). UC is characterised by upregulation of modules involved in antibody production (MZB1, IGJ) and increased metabolic activity (PDK4, ribosomal genes), while PSC differs from UC by interferon (IFIT1) and apoptosis upregulation (G0S2). Supported by machine learning results, PSC and UC are interpreted as molecularly separate entities, while PSC/UC and PSC are indistinguishable.

Overall design

We conducted whole blood RNA-Seq experiments for 495 UC patients, 220 PSC patients (of whom 177 have also a UC diagnosis), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses.

Source Evidence

4 sources
Source Contribution Status
GEO

Original dataset metadata, sample metadata, source links, and GEO data availability flags.

Sample records
1035 GSM samples
 Primary source
recount3

Planned trusted source for processed count availability.

 No match found
Expression Atlas

Planned source for curated expression experiment links.

 No match found
PubMed

Primary GEO citations and related PubMed articles that mention this dataset.

3 linked publications 3 DOIs

Primary publication

  1. Whole blood RNA sequencing identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis. JHEP reports : innovation in hepatology, 2024

Related publications

  1. Long non-coding RNAs in human peripheral blood as biomarkers for age prediction. Forensic science international. Genetics, 2026
  2. Exploring the Clinical Implication of S100A9 in Ulcerative Colitis and Its Progression to Cancer: A Journey from Inflammation to Cancer. International journal of molecular sciences, 2025
Available

Metadata Quality Components

Persisted metadata quality

100 pts
Clarity
100%
Weight
100 pts

Sample source clarity: All samples have source metadata and clear GSE/GSM accessions. Group clarity: Rule-based grouping found both case and control samples. Disease clarity: Disease or condition metadata normalized. Tissue clarity: Anatomical source metadata normalized. Treatment clarity: No unclear treatment split detected in the sample metadata. Replicate clarity: No pooled sample or technical replicate flags detected. Data availability clarity: Dataset-level processed or raw data availability is explicit.

Analysis Readiness

Ready after review
97% DE readiness

Contrast completeness

25/25 pts

Both case and control groups are present in the proposed grouping.

Minimum group size

20/20 pts

Each contrast group has at least 2 samples.

Processed data availability

20/20 pts

Processed data is marked available in the GEO index.

Sample decision clarity

15/15 pts

All samples are assigned to a case or control group.

Blocking warnings

7/10 pts

Warnings are present, but none are critical blockers.

Metadata normalization

10/10 pts

Metadata quality is high enough to support downstream handoff.

Blockers

No readiness blockers detected.

Next Steps

  • Verify the proposed sample assignments and case-versus-control comparison against the GEO metadata before using them in DESeq2 or another differential-expression tool.
  • Confirm processed count files and sample identifiers match the exported metadata.

Analysis Preparation Checklist

5/6 ready

Group labels reviewed

Needs review

Siftome proposed case and control labels, but no reviewer confirmation is stored yet.

Open the sample grouping CSV and confirm group labels before analysis.

Minimum sample count met

Ready

Both groups meet the minimum of 2 samples.

Confirm whether the cohort is large enough for the intended statistical analysis.

Processed counts available

Ready

Processed data availability is marked true in the GEO index.

Verify that downloaded processed files contain usable count or expression identifiers.

Ambiguous samples handled

Ready

No review-needed or unassigned samples are present in the proposed grouping.

Review the grouping table for biologically meaningful differences that the automated checks may not detect.

Exclusion decisions recorded

Ready

No hard-excluded samples were detected by the current rules.

Record any manual exclusions in the downstream analysis notes.

Source traceability preserved

Ready

The dataset and sample accessions can be traced back to GEO.

Keep GEO accessions with exported metadata.

Bioinformatician Review

Standard analyst review

Proceed only after the analyst confirms grouping, exclusions, and source files.

By Siftome standards, no expert review was triggered.

Why This Is Ranked Here

Tumor vs normal
Not suitable Dataset does not meet the current suitability threshold.

Applied Review Decisions

No active review decisions affect this ranking.

Derived Classifications

  • Disease context Ulcerative colitis Disease context came from Normalization rules.
  • Likely case group Ulcerative colitis 715 samples
  • Likely control group Control 320 samples

Intent Interpretation

  • Downgrade or exclusion reason Downgraded for tissue search because it is a biofluid cohort. Derived from current-intent ranking reasons.

Ranking Facts

Supporting evidence

  • Comparison: Disease/model vs control. Specimen: Biofluid. Comparison suitability: 0%.
  • Prioritized assay: bulk RNA-seq is the active assay expectation.
  • Interpreted disease metadata: Ulcerative colitis.
  • Processed data is available for downstream review.
  • External evidence: PubMed links 3 publications; 3 DOIs available: PMID 38304234, PMID 40565156, PMID 41512512.
  • Publication context: Whole blood RNA sequencing identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis.. JHEP reports : innovation in hepatology, 2024. PMID 38304234. DOI 10.1016/j.jhepr.2023.100988.
  • Publication context: Exploring the Clinical Implication of S100A9 in Ulcerative Colitis and Its Progression to Cancer: A Journey from Inflammation to Cancer.. International journal of molecular sciences, 2025. PMID 40565156. DOI 10.3390/ijms26125693.
  • Publication context: Long non-coding RNAs in human peripheral blood as biomarkers for age prediction.. Forensic science international. Genetics, 2026. PMID 41512512. DOI 10.1016/j.fsigen.2025.103419.

Cautions

  • Downgraded for tissue search because it is a biofluid cohort.
  • Disease/control design without a tumor/normal comparison is outside tumor/normal triage.
  • Blood, plasma, or serum cohort downgraded because this ranking targets tissue tumor-vs-normal comparisons.
  • Overall score capped because comparison suitability is weak for the selected search intent.
  • Comparison suitability score is below the Phase 1 recommended threshold.

Dataset Warnings

Normalized Fields

showing 500 of 3604 fields

Sample Group Preview

showing 100 of 1035 preview rows Show Hide
Study totals: Case 715 | Control 320 | Unassigned 0 | Excluded 0 | Ambiguous 0 showing 100 of 1035 preview rows
Group Role Accession Title Source / characteristics Reason
Ulcerative colitis Case GSM5372865 UC001 Whole Blood Disease: UC; Age: 19; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372866 UC002 Whole Blood Disease: UC; Age: 35; Sequencing plate number (used for batch correction): 8 Case marker detected.
Ulcerative colitis Case GSM5372867 UC003 Whole Blood Disease: UC; Age: 59; Sequencing plate number (used for batch correction): 7 Case marker detected.
Ulcerative colitis Case GSM5372868 UC004 Whole Blood Disease: UC; Age: 41; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372869 UC005 Whole Blood Disease: UC; Age: 45; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372870 UC006 Whole Blood Disease: UC; Age: 29; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372871 UC007 Whole Blood Disease: UC; Age: 34; Sequencing plate number (used for batch correction): 8 Case marker detected.
Ulcerative colitis Case GSM5372872 UC008 Whole Blood Disease: UC; Age: 24; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372873 UC009 Whole Blood Disease: UC; Age: 51; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372874 UC010 Whole Blood Disease: UC; Age: 19; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372875 UC011 Whole Blood Disease: UC; Age: 48; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372876 UC012 Whole Blood Disease: UC; Age: 40; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372877 UC013 Whole Blood Disease: UC; Age: 21; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372878 UC014 Whole Blood Disease: UC; Age: 49; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372879 UC015 Whole Blood Disease: UC; Age: 42; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372880 UC016 Whole Blood Disease: UC; Age: 41; Sequencing plate number (used for batch correction): 7 Case marker detected.
Ulcerative colitis Case GSM5372881 UC017 Whole Blood Disease: UC; Age: 33; Sequencing plate number (used for batch correction): 8 Case marker detected.
Ulcerative colitis Case GSM5372882 UC018 Whole Blood Disease: UC; Age: 49; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372883 UC019 Whole Blood Disease: UC; Age: 55; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372884 UC020 Whole Blood Disease: UC; Age: 25; Sequencing plate number (used for batch correction): 8 Case marker detected.
Ulcerative colitis Case GSM5372885 UC021 Whole Blood Disease: UC; Age: 36; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372886 UC022 Whole Blood Disease: UC; Age: 41; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372887 UC023 Whole Blood Disease: UC; Age: 58; Sequencing plate number (used for batch correction): 7 Case marker detected.
Ulcerative colitis Case GSM5372888 UC024 Whole Blood Disease: UC; Age: 19; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372889 UC025 Whole Blood Disease: UC; Age: 19; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372890 UC026 Whole Blood Disease: UC; Age: 65; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372891 UC027 Whole Blood Disease: UC; Age: 51; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372892 UC028 Whole Blood Disease: UC; Age: 33; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372893 UC029 Whole Blood Disease: UC; Age: 47; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372894 UC030 Whole Blood Disease: UC; Age: 43; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372895 UC031 Whole Blood Disease: UC; Age: 71; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372896 UC032 Whole Blood Disease: UC; Age: 48; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372897 UC033 Whole Blood Disease: UC; Age: 18; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372898 UC034 Whole Blood Disease: UC; Age: 20; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372899 UC035 Whole Blood Disease: UC; Age: 27; Sequencing plate number (used for batch correction): 10 Case marker detected.
Ulcerative colitis Case GSM5372900 UC036 Whole Blood Disease: UC; Age: 43; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372901 UC037 Whole Blood Disease: UC; Age: 39; Sequencing plate number (used for batch correction): 12 Case marker detected.
Ulcerative colitis Case GSM5372902 UC038 Whole Blood Disease: UC; Age: 50; Sequencing plate number (used for batch correction): 7 Case marker detected.
Ulcerative colitis Case GSM5372903 UC039 Whole Blood Disease: UC; Age: 51; Sequencing plate number (used for batch correction): 12 Case marker detected.
Ulcerative colitis Case GSM5372904 UC040 Whole Blood Disease: UC; Age: 44; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372905 UC041 Whole Blood Disease: UC; Age: 26; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372906 UC042 Whole Blood Disease: UC; Age: 54; Sequencing plate number (used for batch correction): 12 Case marker detected.
Ulcerative colitis Case GSM5372907 UC043 Whole Blood Disease: UC; Age: 21; Sequencing plate number (used for batch correction): 9 Case marker detected.
Ulcerative colitis Case GSM5372908 UC044 Whole Blood Disease: UC; Age: 21; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372909 UC045 Whole Blood Disease: UC; Age: 37; Sequencing plate number (used for batch correction): 12 Case marker detected.
Ulcerative colitis Case GSM5372910 UC046 Whole Blood Disease: UC; Age: 29; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372911 UC047 Whole Blood Disease: UC; Age: 31; Sequencing plate number (used for batch correction): 13 Case marker detected.
Ulcerative colitis Case GSM5372912 UC048 Whole Blood Disease: UC; Age: 48; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372913 UC049 Whole Blood Disease: UC; Age: 53; Sequencing plate number (used for batch correction): 11 Case marker detected.
Ulcerative colitis Case GSM5372914 UC050 Whole Blood Disease: UC; Age: 44; Sequencing plate number (used for batch correction): 13 Case marker detected.
665 additional case samples are hidden from this preview.
Control Control GSM5372622 Control001 Whole Blood Disease: Control; Age: 29; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372623 Control002 Whole Blood Disease: Control; Age: 46; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372624 Control003 Whole Blood Disease: Control; Age: 39; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372625 Control004 Whole Blood Disease: Control; Age: 44; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372626 Control005 Whole Blood Disease: Control; Age: 58; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372627 Control006 Whole Blood Disease: Control; Age: 34; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372628 Control007 Whole Blood Disease: Control; Age: 26; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372629 Control008 Whole Blood Disease: Control; Age: 41; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372630 Control009 Whole Blood Disease: Control; Age: 57; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372631 Control010 Whole Blood Disease: Control; Age: 47; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372632 Control011 Whole Blood Disease: Control; Age: 36; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372633 Control012 Whole Blood Disease: Control; Age: 70; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372634 Control013 Whole Blood Disease: Control; Age: 49; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372635 Control014 Whole Blood Disease: Control; Age: 68; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372636 Control015 Whole Blood Disease: Control; Age: 55; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372637 Control016 Whole Blood Disease: Control; Age: 58; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372638 Control017 Whole Blood Disease: Control; Age: 60; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372639 Control018 Whole Blood Disease: Control; Age: 55; Sequencing plate number (used for batch correction): 9 Sample-local control marker detected.
Control Control GSM5372640 Control019 Whole Blood Disease: Control; Age: 41; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372641 Control020 Whole Blood Disease: Control; Age: 48; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372642 Control021 Whole Blood Disease: Control; Age: 35; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372643 Control022 Whole Blood Disease: Control; Age: 57; Sequencing plate number (used for batch correction): 9 Sample-local control marker detected.
Control Control GSM5372644 Control023 Whole Blood Disease: Control; Age: 38; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372645 Control024 Whole Blood Disease: Control; Age: 63; Sequencing plate number (used for batch correction): 13 Sample-local control marker detected.
Control Control GSM5372646 Control025 Whole Blood Disease: Control; Age: 45; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372647 Control026 Whole Blood Disease: Control; Age: 70; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372648 Control027 Whole Blood Disease: Control; Age: 71; Sequencing plate number (used for batch correction): 9 Sample-local control marker detected.
Control Control GSM5372649 Control028 Whole Blood Disease: Control; Age: 38; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372650 Control029 Whole Blood Disease: Control; Age: 62; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372651 Control030 Whole Blood Disease: Control; Age: 49; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372652 Control031 Whole Blood Disease: Control; Age: 50; Sequencing plate number (used for batch correction): 12 Sample-local control marker detected.
Control Control GSM5372653 Control032 Whole Blood Disease: Control; Age: 47; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372654 Control033 Whole Blood Disease: Control; Age: 47; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372655 Control034 Whole Blood Disease: Control; Age: 43; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372656 Control035 Whole Blood Disease: Control; Age: 65; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372657 Control036 Whole Blood Disease: Control; Age: 31; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372658 Control037 Whole Blood Disease: Control; Age: 54; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372659 Control038 Whole Blood Disease: Control; Age: 63; Sequencing plate number (used for batch correction): 9 Sample-local control marker detected.
Control Control GSM5372660 Control039 Whole Blood Disease: Control; Age: 34; Sequencing plate number (used for batch correction): 10 Sample-local control marker detected.
Control Control GSM5372661 Control040 Whole Blood Disease: Control; Age: 50; Sequencing plate number (used for batch correction): 9 Sample-local control marker detected.
Control Control GSM5372662 Control041 Whole Blood Disease: Control; Age: 36; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372663 Control042 Whole Blood Disease: Control; Age: 40; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372664 Control043 Whole Blood Disease: Control; Age: 56; Sequencing plate number (used for batch correction): 6 Sample-local control marker detected.
Control Control GSM5372665 Control044 Whole Blood Disease: Control; Age: 46; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372666 Control045 Whole Blood Disease: Control; Age: 54; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372667 Control046 Whole Blood Disease: Control; Age: 67; Sequencing plate number (used for batch correction): 12 Sample-local control marker detected.
Control Control GSM5372668 Control047 Whole Blood Disease: Control; Age: 54; Sequencing plate number (used for batch correction): 8 Sample-local control marker detected.
Control Control GSM5372669 Control048 Whole Blood Disease: Control; Age: 64; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
Control Control GSM5372670 Control049 Whole Blood Disease: Control; Age: 39; Sequencing plate number (used for batch correction): 12 Sample-local control marker detected.
Control Control GSM5372671 Control050 Whole Blood Disease: Control; Age: 33; Sequencing plate number (used for batch correction): 7 Sample-local control marker detected.
270 additional control samples are hidden from this preview.

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