Gut metagenome in colorectal cancer/adenoma, Shanghai, China
99 gut metagenome samples from Shanghai, China, studied as part of a case-control design examining gut microbiota signatures in colorectal precancer and colorectal cancer. machine-written summary
99 samples · 99 runs · CN · Age unknown · 2019 · 12.45 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 495 sample values (collection date, country, latitude, location region, longitude) |
| ✓ Abstract / description | 99 sample values (health condition detail) |
| – Full text | no open-access full text linked |
| – Supplementary tables | no supplementary tables available (or none open access) |
| – External resources | not covered by the external resources we ingest |
| – User contribution | nothing uploaded yet · share metadata |
| – Human verified | not yet checked by a person · I checked this project — verify it |
Genera, mean relative abundance over 86 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 0 | 0% | ||||
| country | 99 | 100% | 99 | |||
| health_condition | 0 | 0% | ||||
| subject_id | 0 | 0% | ||||
| collection_date | 99 | 100% | 99 | |||
| detailed_location | 99 | 100% | ||||
| health_condition_detail | 99 | 100% | 99 | |||
| latitude | 99 | 100% | 99 | |||
| location_region | 99 | 100% | 99 | |||
| longitude | 99 | 100% | 99 |
- Alterations, Interactions, and Diagnostic Potential of Gut Bacteria and Viruses in Colorectal Cancer. 2021 PMID 34307189 PMC8294192 unsure
- Alterations of Gut Mycobiota Profiles in Adenoma and Colorectal Cancer. 2022 PMID 35281451 PMC8908310 unsure
- Metagenomic analysis reveals gut plasmids as diagnosis markers for colorectal cancer. 2023 PMID 37283932 PMC10239823 unsure
- Fusobacterium lineage profiling facilitates the clarification of the associations between non-nucleatum Fusobacterium and colorectal cancer. 2025 PMID 41068096 PMC12511565 unsure
- Distinct prophage infections in colorectal cancer-associated Bacteroides fragilis. 2026 PMID 41654659 PMC12992544 unsure
1 more
- Instance-based transfer learning enables cross-cohort early detection of colorectal cancer. 2026 PMID 42106361 PMC13381771
Archive description
a study of the signatures of gut microbiota in two independent Chinese cohorts of colorectal precancer and CRC and test their utility in detecting colorectal lesions.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by sonnet_x2 with confidence 0.65. Assay shotgun_dna.
- host run.host_tax_id · “9606”
- body site run.scientific_name · “gut metagenome”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN10845054 | collection_date | 2014 | R1 | 0.90 | biosample.attribute:collection_date | 2014 |
| SAMN10845054 | country | CN | R1 | 0.90 | sample.attr.geo_loc_name | China:Shanghai |
| SAMN10845054 | health_condition_detail | mixed_case_control: CRC patients and colorectal precancer vs controls | R4 | 0.50 | study.description | colorectal precancer and CRC and test their utility |
| SAMN10845054 | latitude | 31.0000 | R1 | 0.90 | biosample.attribute:lat_lon | 31 N 121 E |
| SAMN10845054 | location_region | Shanghai | R1 | 0.85 | biosample.attribute:geo_loc_name | China:Shanghai |
| SAMN10845054 | longitude | 121.0000 | R1 | 0.90 | biosample.attribute:lat_lon | 31 N 121 E |
Sequencing
99 runs over 99 samples · mean 12.50 Gbp per run (median 12.45 Gbp, total 1,237.51 Gbp; 99 runs with a base count) · layout PAIRED 99 · platform ILLUMINA 99 · models Illumina HiSeq 2500 (99) · 87% of runs with a Sandpiper profile · first public 2019-02-01
Authors (47)
Gao R first · Zhu Y · Kong C · Xia K · Li H · Zhang X · Liu Y · Zhong H · Yang R · Chen C · Qin N · Qin H last · Wu M · Sun J · Huang L · Wu X · Yin L · Cai Z first · Li P · Zhu W · Wei J · Lu J · Song X · Li K · Li S · Li M last · Wu Y first · Ji G · Han D · Zhang Y · Zhu X · Gao Y · Xie R · Xu M · Lu L · Deng Z · Wei Q · Bi D last · Damgaard F first · Jespersen MG · Møller JK · Coia JE · Dessau RB · Sydenham TV · Strube ML · Møller-Jensen J · Justesen US last
Help complete this project
3 of the 4 core fields are below 50% coverage: age_category, health_condition, subject_id. Share metadata
Downloads
PRJNA514108.csv.gz (3.3 KB) · parquet (73.7 KB) — all 99 samples, every field with route and confidence · PRJNA514108_determinations.csv.gz (3.8 KB) — 594 evidence rows