DRUG-seq service
DRUG-seq boosts screening efforts based on gene expression profiling by offering a unique RNA-seq service that is highly sensitive, extraction-free, massively multiplexed and extremely cost-effective.
DRUG-seq boosts screening efforts based on gene expression profiling by offering a unique RNA-seq service that is highly sensitive, extraction-free, massively multiplexed and extremely cost-effective.
Step 1
Step 2
Step 3
2 days
Step 4
(Qubit, Fragment analyzer, shallow sequencing)
1 week
Step 5
1 week
Step 6
Step 7
Number of samples:
24
Reads per sample in demo dataset:
10'000 reads
To have access to the deep-sequenced dataset (7.3 M reads per sample) contact us.
Demo dataset file size:
13.3 MB
Number of samples:
65
Reads per sample in demo dataset:
10'000 reads
To have access to the deep-sequenced dataset (3.9 M reads per sample) contact us.
Demo dataset file size:
4.76 MB
Number of samples:
24
Reads per sample in demo dataset:
10'000 reads
To have access to the deep-sequenced dataset (7.1 M reads per sample) contact us.
Demo dataset file size:
13.6 MB
Cell line | Species | Tissue | Culture type |
A375 | h.sapiens | Skin, malignant melanoma | adherent |
GM12878 | h.sapiens | PBMC, lymphoblastoid | suspension |
H295R | h.sapiens | Adrenal gland, carcinoma | adherent |
HAP1 | h.sapiens | KBM-7 derived, chronic myelogenous leukemia | adherent |
hASC | h.sapiens | Patient-derived adipose stromal cells | adherent |
hASC-Adipocytes | h.sapiens | Differentiated hASC | adherent |
HEK293 | h.sapiens | Kidney embryonic | adherent |
HeLa | h.sapiens | Cervix, adenocarcinoma | adherent |
HepG2 | h.sapiens | Liver, carcinoma | adherent |
Huh7 | h.sapiens | Liver, carcinoma | adherent |
iNeurons | h.sapiens | Differentiated iPSC | adherent |
MCF-7 | h.sapiens | Breast, adenocarcinoma | adherent |
PANC-1 | h.sapiens | Pancreas, carcinoma | adherent |
U2OS | h.sapiens | Bone, osteosarcoma | adherent |
To guarantee high quality data, we normally request that each sample contains 15k-50k cells/well for 96 well-plate or 2k-10k cells/well for 384 well-plate. The minimum number of cells per pool should be 80k.
DRUG-seq is 3’-end RNA sequencing method and, as such, requires significantly less sequencing as compared to standard full-length RNA-seq in order to reach accurate gene quantification. We therefore normally recommend to sequence 1 to 10 million reads for each sample, which enables the reliable and unbiased detection of over 18’000 genes.
As part of our standard service pipeline, we align the generated data to the genome of choice, provide a detailed report on the alignment and gene counting statistics and, finally, provide ready-to-use gene count matrices for downstream analysis.
Explore the latest, relevant publications in the industry to learn more about DRUG-seq.
Experience reliable, cost-effective, and scalable products that deliver high-quality data for large projects.
Book a one-on-one call with one of our RNA experts to discover how we can assist your next project.