PRJEB7774 ERP008729
Microbiome across colorectal adenoma-carcinoma sequence
Gut microbiome development along the colorectal adenoma-carcinoma sequence
156 stool samples from Austria in a case-control study of healthy controls and patients with advanced colorectal adenoma or carcinoma, tracking gut microbiome changes along the adenoma-carcinoma sequence. machine-written summary
156 samples · 312 runs · AT · Adult · 2015 · 5.00 Gbp / sample · cohort Contributions of Human-Associated Archaeal Metabol
Sources
✓Sequence archive 1,060○Abstract / description○Full text✓Supplementary tables 329✓External resources 402–User contribution–Human verified
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 1,060 sample values (collection date, country, health condition, health condition detail, latitude, location region, longitude) |
| ○ Abstract / description | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC10457972, PMC12035788, PMC12539022, PMC13184533, PMC13281578, PMC7283552, PMC8851854 |
| ✓ Supplementary tables | 329 sample values (age, bmi, sex, subject id) |
| ✓ External resources | 402 sample values (age, antibiotic exposure, bmi, sex) · from curatedMetagenomicData 3 (cMD 3) |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
Samples at a glance
1 sampling locations · 1 country
Age
elderly96
adult60
Condition
colorectal_adenoma47
colorectal_cancer46
healthy_control31
Sex
male88
female68
Country
AT156
Body site
primary156
Sequencing depth per sample · this project all projects
! Self-contradictory metadata
health condition: sequence archive and curatedMetagenomicData disagree for 32 samples (e.g. healthy_control vs cardiometabolic_other) — withheld.
The sources disagree on 32 samples. Where two incompatible values exist for one sample (or one person's samples disagree on sex), neither value is published: the field is left empty here, in the sample sheet and in the downloads. Both sides, with their sources, are in gut_metadata_contradictions.parquet of the data package (what counts as a contradiction).
Contradicted values (32)
| sample | field | value | other value | handling |
|---|---|---|---|---|
| SAMEA3136623 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136624 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136626 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136627 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136628 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136629 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136630 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136634 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136635 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136636 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136640 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136643 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136644 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136648 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136649 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136652 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136653 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136657 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136658 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136659 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136661 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136662 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136663 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136664 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136668 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136670 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136675 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136677 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136678 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3136679 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3178937 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
| SAMEA3178938 | health condition | healthy_control (sequence archive) | cardiometabolic_other (curatedMetagenomicData) | withheld: neither value published |
Community composition
Blautia_A 9.9%Bifidobacterium 5.5%Ruminococcoides 4.5%Gemmiger 4.2%Roseburia 3.8%Faecalibacterium 3.7%Anaerostipes 3.3%Collinsella 2.7%Escherichia 2.7%Bacteroides 2.6%Mediterraneibacter 2.3%Phocaeicola 2.3%not assigned to a genus 5.5%other genera 46.9%
Genera, mean relative abundance over 142 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).
Field coverage
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 156 | 100% | ||||
| country | 156 | 100% | 156 | |||
| health_condition | 124 | 79% | 124 | |||
| subject_id | 109 | 70% | 109 | |||
| age_at_collection_days | 156 | 100% | 156 | |||
| bmi | 156 | 100% | 156 | |||
| collection_date | 156 | 100% | 156 | |||
| detailed_location | 156 | 100% | ||||
| health_condition_detail | 156 | 100% | 156 | |||
| latitude | 156 | 100% | 156 | |||
| location_region | 156 | 100% | 156 | |||
| longitude | 156 | 100% | 156 | |||
| sex | 156 | 100% | 156 | |||
| antibiotic_exposure | 154 | 99% | 154 |
Papers (94)
- HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity. 2020 PMID 32582274 PMC7283552 own_data
- METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks. 2022 PMID 35172890 PMC8851854 own_data
- Gut Microbial and Associated Metabolite Markers for Colorectal Cancer Diagnosis. 2023 PMID 37630597 PMC10457972 own_data
- Association of <i>Fusobacterium nucleatum</i> with colorectal cancer molecular subtypes and its outcome: a systematic review. 2025 PMID 40297307 PMC12035788 own_data
- Gut microbiota alterations and their association with tumorigenic pathways in colorectal cancer: insights from a pooled analysis of 109 microbiome datasets. 2025 PMID 41121269 PMC12539022 own_data
89 more
- DCVBin: a novel binning method for single-sample metagenomes based on DNA language model and variational autoencoder. 2026 PMID 42153323 PMC13184533
- Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. 2016 PMID 27388460 PMC4936053
- Subspecies in the global human gut microbiome. 2017 PMID 29242367 PMC5740502
- Using Decision Tree Aggregation with Random Forest Model to Identify Gut Microbes Associated with Colorectal Cancer. 2019 PMID 30717284 PMC6410271
- Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. 2019 PMID 30936547 PMC7984229
- Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model. 2019 PMID 31068913 PMC6491826
- Clustering co-abundant genes identifies components of the gut microbiome that are reproducibly associated with colorectal cancer and inflammatory bowel disease. 2019 PMID 31370880 PMC6670193
- Beyond Taxonomic Analysis of Microbiomes: A Functional Approach for Revisiting Microbiome Changes in Colorectal Cancer. 2019 PMID 32038558 PMC6990412
- Resurrection of a global, metagenomically defined gokushovirus. 2020 PMID 32101162 PMC7062461
- Host DNA contents in fecal metagenomics as a biomarker for intestinal diseases and effective treatment. 2020 PMID 32393180 PMC7216530
- Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning. 2020 PMID 32534441 PMC7298543
- Establishing a novel colorectal cancer predictive model based on unique gut microbial single nucleotide variant markers. 2021 PMID 33430705 PMC7808391
- Metagenome Analysis of Intestinal Bacteria in Healthy People, Patients With Inflammatory Bowel Disease and Colorectal Cancer. 2021 PMID 33738265 PMC7962608
- Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. 2021 PMID 33944776 PMC8096432
- Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models. 2021 PMID 33947803 PMC8269207
- Compositional and genetic alterations in Graves' disease gut microbiome reveal specific diagnostic biomarkers. 2021 PMID 34079079 PMC8528855
- The taxonomic distribution of histamine-secreting bacteria in the human gut microbiome. 2021 PMID 34563136 PMC8465708
- MetaGeneBank: a standardized database to study deep sequenced metagenomic data from human fecal specimen. 2021 PMID 34592929 PMC8485520
- Characterizing Enterotypes in Human Metagenomics: A Viral Perspective. 2021 PMID 34659174 PMC8511818
- Expanding the Colorectal Cancer Biomarkers Based on the Human Gut Phageome. 2021 PMID 34935421 PMC8693921
- Species-Level Analysis of the Human Gut Microbiome Shows Antibiotic Resistance Genes Associated With Colorectal Cancer. 2021 PMID 34975790 PMC8715872
- Towards a metagenomics machine learning interpretable model for understanding the transition from adenoma to colorectal cancer. 2022 PMID 35013454 PMC8748837
- Multi-kingdom microbiota analyses identify bacterial-fungal interactions and biomarkers of colorectal cancer across cohorts. 2022 PMID 35087227 PMC8813618
- Evaluating supervised and unsupervised background noise correction in human gut microbiome data. 2022 PMID 35130266 PMC8853548
- Increasing prediction performance of colorectal cancer disease status using random forests classification based on metagenomic shotgun sequencing data. 2022 PMID 35155839 PMC8801753
- Contributions of Human-Associated Archaeal Metabolites to Tumor Microenvironment and Carcinogenesis. 2022 PMID 35225671 PMC9045267
- Integrated metagenomics identifies a crucial role for trimethylamine-producing Lachnoclostridium in promoting atherosclerosis. 2022 PMID 35273169 PMC8913745
- Diversity and distribution of sulfur metabolic genes in the human gut microbiome and their association with colorectal cancer. 2022 PMID 35440042 PMC9016944
- Metagenomic assembled plasmids of the human microbiome vary across disease cohorts. 2022 PMID 35654877 PMC9163076
- Identification and Characterization of Major Bile Acid 7α-Dehydroxylating Bacteria in the Human Gut. 2022 PMID 35736002 PMC9426597
- Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes. 2022 PMID 36077748 PMC9454621
- Meta-analysis of fecal viromes demonstrates high diagnostic potential of the gut viral signatures for colorectal cancer and adenoma risk assessment. 2023 PMID 36198381 PMC10334131
- Faecal microbiome-based machine learning for multi-class disease diagnosis. 2022 PMID 36357393 PMC9649010
- Machine learning for data integration in human gut microbiome. 2022 PMID 36419034 PMC9685977
- The microbiome's fiber degradation profile and its relationship with the host diet. 2022 PMID 36464700 PMC9721016
- Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population. 2022 PMID 36564713 PMC9789565
- Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database. 2022 PMID 36564826 PMC9784093
- Using whole-genome sequencing (WGS) to plot colorectal cancer-related gut microbiota in a population with varied geography. 2022 PMID 36578080 PMC9795735
- Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype. 2023 PMID 36706753 PMC9975273
- 2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo. 2023 PMID 36984891 PMC10059959
- Toward an improved definition of a healthy microbiome for healthy aging. 2022 PMID 37118093 PMC10154212
- Metagenomic analysis reveals gut plasmids as diagnosis markers for colorectal cancer. 2023 PMID 37283932 PMC10239823
- Multimodal metagenomic analysis reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer. 2023 PMID 37635357 PMC10464540
- Machine learning approaches in microbiome research: challenges and best practices. 2023 PMID 37808286 PMC10556866
- Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies. 2023 PMID 37844077 PMC10602384
- Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach. 2023 PMID 37905808 PMC10734426
- Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts. 2023 PMID 37932270 PMC10628233
- The Archaeome's Role in Colorectal Cancer: Unveiling the DPANN Group and Investigating Archaeal Functional Signatures. 2023 PMID 38004753 PMC10673094
- Multi-kingdom microbial signatures in excess body weight colorectal cancer based on global metagenomic analysis. 2024 PMID 38182885 PMC10770074
- <i>Anaerostipes hadrus</i>, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil. 2024 PMID 38470044 PMC11036815
- Tracking and characterization of a novel conjugative transposon identified by shotgun transposon mutagenesis. 2024 PMID 38601936 PMC11005914
- Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseases. 2024 PMID 38605009 PMC11009399
- Establishing a novel inflammatory bowel disease prediction model based on gene markers identified from single nucleotide variants of the intestinal microbiota. 2022 PMID 38868717 PMC10989788
- Enhancing insights into diseases through horizontal gene transfer event detection from gut microbiome. 2024 PMID 38884260 PMC11317153
- Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases. 2024 PMID 39078158 PMC11334437
- Is There an Interplay between Environmental Factors, Microbiota Imbalance, and Cancer Chemotherapy-Associated Intestinal Mucositis? 2024 PMID 39204125 PMC11357004
- An expanded database and analytical toolkit for identifying bacterial virulence factors and their associations with chronic diseases. 2024 PMID 39278950 PMC11402979
- Colorectal cancer-associated bacteria are broadly distributed in global microbiomes and drivers of precancerous change. 2024 PMID 39384807 PMC11464690
- Oral Microbial Translocation Genes in Gastrointestinal Cancers: Insights from Metagenomic Analysis. 2024 PMID 39458395 PMC11510655
- RFW captures species-level metagenomic functions by integrating genome annotation information. 2024 PMID 39662474 PMC11704624
- Systematic identification of secondary bile acid production genes in global microbiome. 2025 PMID 39688414 PMC11748489
- Impact of simulation and reference catalogues on the evaluation of taxonomic profiling pipelines. 2025 PMID 39804694 PMC11728698
- The physical biogeography of <i>Fusobacterium nucleatum</i> in health and disease. 2025 PMID 40062772 PMC11980382
- Transmission of antimicrobial resistance genes from the environment to human gut is more pronounced in colorectal cancer patients than in healthy subjects. 2025 PMID 40236771 PMC11995172
- Microbes with higher metabolic independence are enriched in human gut microbiomes under stress. 2025 PMID 40377187 PMC12084026
- Metagenomics reveals an increased proportion of an <i>Escherichia coli</i>-dominated enterotype in elderly Chinese people. 2025 PMID 40436643 PMC12119184
- Pooled analysis of 3,741 stool metagenomes from 18 cohorts for cross-stage and strain-level reproducible microbial biomarkers of colorectal cancer. 2025 PMID 40461820 PMC12283368
- Individualized metagenomic network model for colorectal cancer diagnosis: insights into viral regulation of gut microecology. 2025 PMID 40462511 PMC12133679
- Cross-cohort analysis identifies shared gut microbial signatures and validates microbial risk scores for colorectal cancer. 2025 PMID 40528214 PMC12175378
- Phylogroup Homeostasis of <i>Escherichia coli</i> in the Human Gut Reflects the Physiological State of the Host. 2025 PMID 40732093 PMC12299893
- Metabolic cross-feeding of a dietary antioxidant enhances anaerobic energy metabolism by human gut bacteria. 2025 PMID 40763732 PMC12683948
- Lipid accumulation inhibition strategies alleviate Fusobacterium nucleatum-infected colorectal cancer. 2025 PMID 40770383 PMC12326762
- Highly-accurate prediction of colorectal cancer through low abundance uncultivated genomes recovered using metagenomic co-assembly and binning approach. 2025 PMID 40973961 PMC12449802
- Fusobacterium lineage profiling facilitates the clarification of the associations between non-nucleatum Fusobacterium and colorectal cancer. 2025 PMID 41068096 PMC12511565
- Multi-cohort metagenomics reveals strain functional heterogeneity and demonstrates fecal microbial load correction improves colorectal cancer diagnostic models. 2025 PMID 41070134 PMC12504321
- Phylo-Spec: a phylogeny-fusion deep learning model advances microbiome status identification. 2025 PMID 41283667 PMC12710343
- Distinct prophage infections in colorectal cancer-associated Bacteroides fragilis. 2026 PMID 41654659 PMC12992544
- Cross-domain metabolic interactions link Methanobrevibacter smithii to colorectal cancer microbial ecosystems. 2026 PMID 41720792 PMC13035836
- The landscape of tissue-resident microbiota across normal, polyp, and colorectal cancer tissues. 2026 PMID 41730886 PMC13039525
- Identifying Cytokine Motif-Containing, Immunomodulatory Bacterial Proteins in Human Gut Microbiome. 2026 PMID 41869887 PMC13205780
- Landscape of flavonoid metabolism in human gut microbiome and its association with health and disease. 2025 PMID 41909884 PMC12940152
- Multi-cohort analysis of metagenome for type 2 diabetes identified universal gut microbiota signatures across populations. 2026 PMID 41927536 PMC13057204
- Instance-based transfer learning enables cross-cohort early detection of colorectal cancer. 2026 PMID 42106361 PMC13381771
- Network topology of the gut microbiome associates with metabolic health in obesity. 2026 PMID 42129189 PMC13172010
- Gut fungal signatures in colorectal cancer and their potential for supporting diagnosis: a multi-cohort metagenomic analysis. 2026 PMID 42271362 PMC13281578
- Obesity-driven microbial GABA depletion promotes metabolic rewiring and colorectal cancer progression. 2026 PMID 42503520 PMC13402817
- Metagenome analysis reveals multi-kingdom gut microbiota as diagnostic markers for colorectal cancer. 2026 PMID 42519695 PMC13383993
- Fedflow: cloud orchestration for federated learning with the FeatureCloud platform. 2026 PMID 42725323 PMC13561539
- Plasmid dispersal and recombination across human gut microbiomes is neutral, but overpowered by inflammatory diseases 2023
Details
Archive description
Colorectal cancer, a commonly diagnosed cancer in the elderly, often develops slowly from benign polyps called adenoma. The gut microbiota, with its critical roles in nutrient metabolism and immune modulation, is believed to be directly involved in colorectal carcinogenesis. The identity and functional capacity of the adenoma- or carcinoma-related gut microbe(s), however, have not been surveyed in a comprehensive manner. Here we perform metagenomewide association study (MGWAS) on stools from healthy controls, advanced adenoma and carcinoma patients, revealing gene markers from over 100 bacterial strains enriched in each group.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult and elderly by deterministic_prior with confidence 0.90. Assay shotgun_dna.
- host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- body site study.title · “Gut microbiome development along”
- body site study.description · “Colorectal cancer, a commonly”
- life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- life stage study.description · “cancer in the elderly , often develops”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA3136623 | age_at_collection_days | 26663 | R2 | 0.85 | paper.supp.13099_2025_712_MOESM7_ESM.xlsx[Sheet1!Age (yrs)] | 73 |
| SAMEA3136680 | age_at_collection_days | 24837.0 | R2 | 0.75 | external.cmd source | age: 68; age_unit: Year; age_group: Elderly |
| SAMEA3136623 | antibiotic_exposure | no | R2 | 0.75 | external.cmd source | antibiotics_current_use: No |
| SAMEA3136623 | bmi | 32.0 | R2 | 0.85 | paper.supp.13099_2025_712_MOESM7_ESM.xlsx[Sheet1!BMI] | 32 |
| SAMEA3136680 | bmi | 34.01 | R2 | 0.75 | external.cmd source | bmi: 34.01 |
| SAMEA3136623 | collection_date | 2013 | R1 | 0.90 | biosample.attribute:collection_date | 2013 |
| SAMEA3136623 | country | AT | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea | Austria |
| SAMEA3136625 | health_condition | healthy_control | R1 | 0.85 | biosample.attribute:title | Stool sample from controls |
| SAMEA3136623 | health_condition_detail | Stool sample from controls | R1 | 0.85 | biosample.attribute:title | Stool sample from controls |
| SAMEA3136623 | latitude | 47.8015 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 47.80151 13.04292 |
| SAMEA3136623 | location_region | Salzburg | R1 | 0.60 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 47.80151 13.04292 |
| SAMEA3136623 | longitude | 13.0429 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 47.80151 13.04292 |
| SAMEA3136623 | sex | female | R2 | 0.75 | external.cmd source | sex: Female |
| SAMEA3136625 | sex | female | R2 | 0.85 | paper.supp.13099_2025_712_MOESM7_ESM.xlsx[Sheet1!Gender (1:male, 2:female)] | ERR688409: 2 |
| SAMEA3136623 | subject_id | 31766 | R2 | 0.85 | paper.supp.13099_2025_712_MOESM8_ESM.xlsx[Sheet1!Sample Id] | ERR688419: 31766 |
Sequencing
312 runs over 156 samples · mean 2.50 Gbp per run (median 1.57 Gbp, total 778.91 Gbp; 312 runs with a base count) · layout PAIRED 156, SINGLE 156 · platform ILLUMINA 312 · models Illumina HiSeq 2000 (312) · 46% of runs with a Sandpiper profile · first public 2015-03-05
Authors (79)
Tarracchini C first · Fontana F · Mancabelli L · Lugli GA · Alessandri G · Turroni F · Ventura M · Milani C last · Orihara K first · Yahagi K · Saito Y · Watanabe Y · Sasai T · Hara T · Tsukuda N · Oki K · Fujimoto J · Matsuki T last · Ormaasen I first · Rudi K · Diep DB · Snipen L last · De Biase R · Bocchio F · Viappiani A · De Conto F · Nouvenne A · Ticinesi A · Bussolati O · Meschi T · Cecchi R · van Sinderen D · Haque S first · Bantun F · Jalal NA · Faidah H · Babalghith AO · Alobaidy MA · Aldairi AF · Ahmad F last · Dong Y first · Wang M · Zhou X · Wang P · Yan K · Wang S · Zhong JC · Li H · Zhao L · Li B · Li J last · Schroer HW first · Beghini F · Raygoza Garay JA · Christakis NA · Bosch DE last · Zhang Z first · Lu T · Dong B · Liu J · Zhang Y · Li S · Liu H · Li X · Guan T · Guo H · Yan Q · Lei Z · Yu X · Wang L · Kang J · Li L · Zhao D last · Weilguny L first · Probul N · Ren Y · Pons N · Baumbach J · Almeida M last
Downloads
PRJEB7774.csv.gz (6.1 KB) · parquet (78.6 KB) — all 156 samples, every field with route and confidence · PRJEB7774_determinations.csv.gz (18.4 KB) — 1,791 evidence rows
Samples (156 · every field this project has values for · hover a cell for its source)
Loading the sample table…