RNA sequencing analysis of isoginkgetin and thapsigargin treated HCT116 and HCT116 ATF4 deficient cells
RNA-seq (gene expression) · human · 48 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 48 samples: 48 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Activating transcription factor 4 plays a major role in shaping the transcriptional response to isoginkgetin in HCT116 cellsScientific reports · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE249009_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1047008 and SRA study SRP475085. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7924587 2-1-25_2h_DMSO_3_18_22_S11
- GSM7924588 2-1-25_2h_DMSO_3_23_22_S31
- GSM7924589 2-1-25_2h_DMSO_3_25_22_S46
- GSM7924590 2-1-25_2h_DMSO_3_31_22_S9
- GSM7924591 2-1-25_2h_Tg_3_18_22_S18
- GSM7924592 2-1-25_2h_Tg_3_23_22_S38
- GSM7924593 2-1-25_2h_Tg_3_25_22_S14
- GSM7924594 2-1-25_2h_Tg_3_31_22_S16
- GSM7924595 2-1-25_8h_DMSO_3_18_22_S21
- GSM7924596 2-1-25_8h_DMSO_3_23_22_S10
- GSM7924597 2-1-25_8h_DMSO_3_25_22_S34
- GSM7924598 2-1-25_8h_DMSO_3_31_22_S36
- GSM7924599 2-1-25_8h_I30_3_18_22_S33
- GSM7924600 2-1-25_8h_I30_3_23_22_S7
- GSM7924601 2-1-25_8h_I30_3_25_22_S42
- GSM7924602 2-1-25_8h_I30_3_31_22_S30
- GSM7924603 2-1-25_8h_ND_3_18_22_S40
- GSM7924604 2-1-25_8h_ND_3_23_22_S25
- GSM7924605 2-1-25_8h_ND_3_25_22_S15
- GSM7924606 2-1-25_8h_ND_3_31_22_S41
- GSM7924607 2-1-25_8h_Tg_3_18_22_S19
- GSM7924608 2-1-25_8h_Tg_3_23_22_S2
- GSM7924609 2-1-25_8h_Tg_3_25_22_S23
- GSM7924610 2-1-25_8h_Tg_3_31_22_S12
- GSM7924611 HCT116_2h_DMSO_3_18_22_S4
- GSM7924612 HCT116_2h_DMSO_3_23_22_S47
- GSM7924613 HCT116_2h_DMSO_3_25_22_S27
- GSM7924614 HCT116_2h_DMSO_3_31_22_S44
- GSM7924615 HCT116_2h_Tg_3_18_22_S8
- GSM7924616 HCT116_2h_Tg_3_23_22_S28
- GSM7924617 HCT116_2h_Tg_3_25_22_S6
- GSM7924618 HCT116_2h_Tg_3_31_22_S5
- GSM7924619 HCT116_8h_DMSO_3_18_22_S26
- GSM7924620 HCT116_8h_DMSO_3_23_22_S20
- GSM7924621 HCT116_8h_DMSO_3_25_22_S39
- GSM7924622 HCT116_8h_DMSO_3_31_22_S3
- GSM7924623 HCT116_8h_I30_3_18_22_S22
- GSM7924624 HCT116_8h_I30_3_23_22_S32
- GSM7924625 HCT116_8h_I30_3_25_22_S13
- GSM7924626 HCT116_8h_I30_3_31_22_S37
+ 8 more — browse all 48 samples with per-sample file links →
- GSE254323 RNA-seq of colorectal cancer cell line HCT116 and DLD-1 cells treated with PRIMA-1met or oxaliplatin or combination therapy 24 samples shares hct116, treated
- GSE308646 Combined Targeting of de novo Pyrimidine Synthesis and ATR Promotes ATF4-Mediated Cell Death in TP53-Deficient ALL 24 samples shares atf4, deficient
- GSE335198 RNA-seq and ONT full-length transcriptome profiling of HCT116 and WiDr cells treated with DMSO, GSK025, or GSK715 19 samples shares hct116, treated
- GSE306466 RNA-seq of dTAG-NUDT21 HCT116 cells treated with DMSO+JTE-607 or dTAGV1+JTE-607. 8 samples shares hct116, treated
- GSE324253 RNA-seq in HCT116 cells treated with coptisine 6 samples shares hct116, treated
- GSE318306 Whole transcriptome sequencing of HCT116 cells with altered DNA repair capacities treated with RTX or 5FdUR 36 samples shares hct116, treated
- GSE262938 ChIP-seq of BRD4 of HCT116 cells treated with MZ1 or PDD00017273 6 samples shares hct116, treated
- GSE281511 RNA seq of liver cancer cells treated with different concentration gradients of Thapsigargin (TG), Tunicamycin (TM), and FCCP 44 samples shares thapsigargin, treated
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.