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Yes, you can process one to four samples simultaneously. For the unused channels, we provide proxy chips to compensate for the lack of samples.

No, reusing the chips is not an option. Please, always use new chips for your single cells experiments to avoid cross-contamination and ensure the best quality of the processing and results.

The Matrix Neo takes a single-cell suspension as input and produces bead-bound mRNA as output. Proceed immediately to the reverse transcription steps.

The PythoN comes preloaded with some recommended programs. Additionally, there are several suggested programs for different tissue types that have been tested by us.

Yes, we have experience and dedicated programs for some organoids. Nonetheless, depending on the nature of the sample, it might require optimization.

The PythoN tissue dissociation tubes are designed to be single-use only. We cannot guarantee the integrity of the tubes if they are used more than once. Additionally, we cannot guarantee that no cross-contamination would occur if the tubes are used more than once.

Single Cell Kits

The recommended captured cell number varies according to the chip used:

  • Standard Density (SD) Chip: 3000-10000 cells.
  • High Density (HD) Chip: 9000-30000 cells.
  • Large Well (LW) Chip: 1500-3000 cells.

However, the captured cell number can be increased by using multiplexing (see CLindex FAQ).

We capture the transcriptome from individual cells via the Poly-A tail, therefore performing 3´ sequencing. However, for the other libraries we utilize different strategies, such as probe-based capture (V(D)J and FocuSCOPE) and 5’ sequencing (sCircle).

The distribution of the beads inside the GEXSCOPE chip follows a normal Poisson distribution, and thus we can keep a low doublet rate at various loading densities (less than 5% at the maximum capture rate for the SD chip).

While single cells provide more information (transcripts in the nucleus and the cytoplasm), sometimes they are difficult to isolate and process due to several factors (for instance, freezing tissues damages the integrity of the cell membrane and adipocytes are too light and large to be captured in the microwells). In these cases, it is beneficial to isolate single nuclei. In turn, some cell types might be more difficult to isolate, creating a bias towards the easy-to-isolate cells. Using single nucleus RNA seq, this bias is reduced.

Yes, you can use sorted nuclei as input material. In this case, we strongly recommend measuring the nucleus concentration and stability after the sorting, to ensure that the input material is good quality and meets the loading requirements (since the FACS sorting might lower the stability and viability of the soothed material and the counting from the sorter might not be accurate).

Debris has many origins and causes which may be of cellular or acellular origin (such as components of the extracellular matrix). In any case, debris can occupy the microwells and contribute to background in the results. In all cases, running the samples through a cell strainer (30 µm) can reduce the debris. In the case of brain samples, debris is most likely myelin and there are specific kits that aim to get rid of myelin contamination (such as the bead-based Myelin Isolation reagents on the market). Using gradients such as Percoll®, Ficoll, OptiPrep™ or a modified sucrose gradient can also help. Finally, finding the right solution should be done on a sample-by-sample basis.

The kit includes reagents, beads and chips that are needed for enzymatic nucleus isolation, lysis, mRNA capture, and library preparation. Other items that may be useful for the isolation of nuclei, such as mortar, pestle or dounce homogenizer, are not included.

The GEXSCOPE Microbial Single Cell RNA Library Kit is intended to be used only with yeast samples. The kit has been tested with Saccharomyces cerevisae, Rhodosporidium toruloides, and Candida albicans. Any other uses cannot be guaranteed and should be tested by the user.

GEXSCOPE Single Cell V(D)J Kit provides information on the clonotypes of the T/B cell, but not the isotypes. This would require information from the constant region on the full-length V(D)J, which can be obtained using our sCircle kit. For the gamma and delta chains, theoretically, we could get information of these chains from cell annotation data, provided by good sample quality.

With the GEXSCOPE Single Cell V(D)J Kit you will capture the CDR3 region of the TCR and/or BCR.

The kit is available only for human samples.

You can prepare both TCR and BCR from the same sample. Therefore, you will need to prepare two or three libraries (one transcriptome and one library each for TCR and BCR), depending on the experimental question.

The metabolic labeling must be adjusted for different samples. The recommended labeling time is around 0.5-4h based on the transcriptional activity of the cells. We suggest starting with an incubation time of 2 hours and adjusting accordingly. Increasing the labeling time beyond 4 hours might help to ensure a good conversion rate, but it might be detrimental to the health of the animal or the quality of the cells.

You do not need to use a control sample, since our bioinformatics pipeline can do the analysis without it. However, including a control sample will give more resolution to the analysis, increasing the quality of the results.

The T to C conversion rate will vary depending on different factors, mainly the labeling time. The background conversion, in comparison with the reference genome, is usually lower than ~0.2%. A T-to-C conversion rate of ~0.8% or higher is enough to detect transcriptional dynamics in your sample.

Yes, you can inspect the dynamics of gene expression for specific genes and cells.

We have pre-constructed panels for Lung Cancer, Blood Cancer, Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Epstein Bar Virus (EBV). The targeted genes and fusion genes are.

Yes, if you need to target specific genes, which are not included in the pre-constructed panels, we can create a customized FocuSCOPE Kit targeting up to 10 specific targets. Please contact our sales colleagues in your area for the requirements.

Since labeling requires several washing steps, we recommend starting with more than one million cells, with at least 85% viability, to ensure keeping enough cells to run the experiment.


The Glycosylation label (ProMoSCOPE tag) covalently binds N-Acetyllactosamine (LacNAc) at the cell surface.

sCircle is intended to sequence full-length TCR or BCR (i.e. V(D)J and part of the constant region).

sCircle Single Cell Full-Length TCR/BCR Kit is available for human or mouse samples. The kit relies on poly-A capture followed by enrichment of the TCR/BCR regions using specific primers. For now, we have primers/kits with human- and mouse-specificity. We are constantly adding compatibility with other species to our kits and will update this information accordingly. If you have any wishes, please contact us

sCircle Single Cell Full-Length TCR/BCR Kit is available for TCR or BCR library preparation. Therefore, you will need to prepare two libraries: one for the transcriptome and one for the receptor (TCR or BCR).

Yes, the sequences covered by the sCircle kit allows you to extract information about the isotypes.

The kits contain 16 tags for a maximum of 16 simultaneous samples. The 1-rxn kit will contain enough of each of the 16 tags for one labeling run. Therefore, you can either run one experiment of 16 samples or 2 experiments of 8 or 4 experiments of 4.

Since labeling requires several washing steps, we recommend starting with more than one million cells per sample, with at least 85% viability, to ensure keeping enough cells to run the experiment.

CLindex cannot be used for single nuclei samples, since the labeling is done at the membrane surface level.

CLindex multiplexing kit can label up to 16 different samples, which theoretically allows you to load up to 160000 cells with a 28% identifiable doublet rate (which can be filtered out during the analysis workflow). Our recommendation is to not go above 120000 cells to load the HD chip.

We have extensively tested our dissociation buffer with various organs of human and mouse origin. However, we have also used it with other species such as zebrafish (Danio rerio) and other rodents.

Our preservation buffer is designed to preserve fresh tissues, maintaining the constituent cell viability for up to 72 hours. We have found that organoids can be safely stored and transported in their own medium – including matrigel — at ambient temperatures without significant loss of viability.

No. We find that the best solution for cell suspensions is cryopreservation for transportation or storage. Please be sure to check the best cryopreservation medium for your particular type of cells and also please be aware that we cannot guarantee the loss of some subtypes upon freezing.

AccuraCode is designed to work with cell lines. Nonetheless, it can be used with other cell types, although this would require some optimization in terms of number of cells loaded and efficiency of cell lysis.

The size of the microwells in the LW chip is 100 µm in diameter, and 100 µm in height.

With the LW chip you can capture 1500 to 3000 cells.

The LW chip is recommended for cells bigger than 25µm diameter, or irregular (not round shaped) cells such as adult cardiomyocytes.

Unfortunately, currently there is no LW chip version for the Matrix NEO automated system, and it can only be operated manually.


We offer bioinformatic solutions to cover all the needs related to Singleron´s kits:

  • CeleScope: preprocessing software for Singleron´s Kits. CeleScope is an automated pipeline that takes the raw fastq files as input and correctly detects the utilized chemistry, does barcode demultiplexing, quality and adapter trimming, mapping to the reference genome, and cell calling. It outputs a gene count matrix compatible with our SynEcoSys and the most popular downstream analysis software packages (e.g. Seurat).
  • SynEcoSys: data analysis pipeline integrated with an extensive manually curated single cell database. SynEcoSys performs cell annotation using the popular CellID package with publicly available database or with our manually curated database. It also allows various QC filtering steps as well as performing differential gene expression analysis.
  • CeleViz: freely available standalone single cell data visualization tool.
  • Personalized solutions

Although possible, it is not recommended to run CeleScope on a normal desktop/laptop. We recommend running CeleScope on a workstation, a computing cluster or using a cloud computing provider such as Google Cloud or Amazon Web Service (AWS). The mapping step in particular requires a lot of memory (minimum of 32 GB but ideally 64 GB). Furthermore, the raw data fastq files as well as the mapping files are huge (in the order of tens to hundreds of gigabytes) and will quickly eat up your storage space. We also recommend installing CeleScope in its own conda environment to avoid clashes with other preinstalled packages.

There was a major overhaul of the CeleScope code base with v.2 to make it faster and more efficient. The downside to that is the report you get in the end looks different from the previous versions. Rest assured the gene count matrices are still in the same format and compatible with popular software packages such as Seurat. We recommend upgrading to the latest version of CeleScope but if you have started a project with the previous versions, you can continue using it for consistency.

The input files for CeleScope are:

  • Sequencing FASTQ files.
  • Reference genome FASTA file.
  • Reference genome annotation GTF file.

The fasta and gtf files need to be indexed beforehand as mentioned on the CeleScope GitHub page. Please be aware that due to the overhaul of the CeleScope code base, if you have recently upgraded from v.1.x to v.2.x, you will need to reindex your reference fasta and gtf files before using CeleScope for the first time.

The main output files of CeleScope are:

  • HTML QC report, including the main metrics for: sequencing, demultiplexing, trimming, alignment to reference genome, annotation and cell calling.
  • Count matrix: file containing the transcript (UMI) counts for every gene and barcode corresponding to a cell in the cell calling.

Yes, you can use the count matrix generated with CeleScope as input for SynEcoSys.

Currently, SynEcoSys does not allow multiple datasets integration. Only 2-way comparisons are possible at the moment.

Homo sapiens, Mus musculus, Macaca fascicularis, Macaca mulatta, and Chlorocebus sabaeus.

Our Bioinformaticians update SynEcoSys database on a weekly basis. Still, due to the increasing number of single cell publications, some publicly available data might not yet be included in the database. If you are interested in a specific dataset, please contact us and we will include it in SynEcoSys as soon as possible.

Singleron has a strong team of bioinformaticians with years’ worth of experience in single-cell sequencing analysis. Please contact us with information about your project and they will be happy to set up a meeting with our experts to discuss your project and how they can help.

QC criteria

We do not recommend re-amplifying the cDNA for library preparation and sequencing, since this might increase the PCR bias towards more abundant transcripts. An exception to this is the cDNA used for targeted or enriched products, such as in sCircle Single Cell Full-Length TCR/BCR Kit, where the cDNA amount needed to produce the receptor libraries is much higher.

Although it is lower than our recommendation, if necessary, it is possible to use less than 10ng cDNA for library preparation. In this case, to ensure enough library yield, increase 1-2 cycles in the library amplification PCR.

There are some cases where we will observe unexpected fragments in the cDNA suspension:

  • Small and sharp fragments might indicate primer dimers and might be removed doing further purification using AmPure beads.
  • Sharp peaks around 700bp might indicate RBC contamination, and this will be considered in the sequencing and data analysis. Alternatively, if the viability was suboptimal those peaks might indicate high mitochondrial content.


As our chip is an open system, it allows some changes to meet the needs of each experiment. In this regard, a different buffer can be used (for example W5 buffer for protoplasts) when it doesn’t contain metal chelator agents that might interfere with the reverse transcription (such as EDTA), and it must be RNAse free. In this case, we recommend following these steps:

  1. Wash the chip with your own buffer prior to cell loading.
  2. Load the cells, which are in suspension in your own buffer.
  3. Wash the chip with PBS to get rid of the excess cells that are not within microwells, following the handbook instructions.
  4. Load the beads (resuspended in 60ul of PBS), following the handbook instructions.
  5. Add the lysis buffer and continue with the instructions as described in the handbook.

To ensure the best handling of the SCOPE-chip, please use one of our recommended pipette tips:

  • Biofil PMT231200
  • Eppendorf cat #0030078551
  • VWR cat #732-3701

Due to the design of the chip, background noise from ambient RNA is very low. In addition, no spillover of RNA between wells was detected since wells containing only the beads had no RNA detected above the ambient level cutoff.

We performed a comparison study between our single-cell cell workflow, which utilizes beads, and bulk sequencing, which does not. The data quality was comparable, providing evidence that beads are harmless to cells.

To avoid too similar UMIs within the same bead, we use 10^6-10^7 UMIs per bead, and the possible different combinations are 4^12.

GEXSCOPE v3.0.1 structure (single-cell/single-nucleus/VDJ/FocuSCOPE/PromoSCOPE/DynaSCOPE latest chemistry): BC1(9nt)-Linker1(16nt)-BC2(9nt)-Linker2(16nt)-BC3(9nt)-UMI(12nt)-PolyT(18nt). barcode (BC) and linker whitelists can be found at: There you can also find the structure of the previous chemistry versions.

sCircle (transcriptome): BC1(8nt)-Linker1(16nt)-BC2(8nt)-Linker2(16nt)-BC3(8nt)-Linker(1nt)-UMI(12nt)-PolyT(18nt). The barcode (BC) and linker whitelists can be found at:

sCircle (VDJ): UMI(9nt)-BC1(8nt)-Linker1(16nt)-BC2(8nt)-Linker2(16nt)-BC3(8nt). The barcode (BC) and linker whitelists can be found at:


With a service project we can cover the whole Singleron workflow from tissue dissociation to single cell or single nuclei up to sequencing results and data preprocessing.

From receiving the sample in our facility, we will obtain the sequencing results and data preprocessing no later than 7 weeks.

Yes, you will be notified with our QC reports in every step of the service process.


Yes, our system is compatible with CITEseq protein profiling. We have published an application note on combining CITEseq with our protocol.

We have experience with a wide range of species, including Homo sapiens, Mus musculus, Danio rerio, Drosophila melanogaster, Arabidopsis thaliana, Populus tremula, Physcomitrium patens, and Saccharomyces cerevisiae samples.

Currently, we cannot process FFPE samples. However, we have experience with methanol-fixed samples, although it might require some optimization depending on the sample type.

Yes, you can use FACS or MACS sorted cells as input material. In this case, we strongly recommend measuring the cell concentration and viability after the sorting, to ensure that the input material is of good quality and meets the loading requirements (since the counting from the sorter is usually not well estimated).


Our platform is comparable to Illumina TruSeq, except for sCircle library, which is compatible with Nextera.

We have both options: single and dual indexes.

PhiX is added for two main reasons: to ensure the heterogeneity of sequenced bases during the run and as a means of obtaining QC metrics during the run. Since we are sequencing transcriptomes, we have no problems with the heterogeneity of sequenced regions and, technically, the PhiX is not necessary. However, we recommend including a PhiX spike-in as a measure of the quality of the run (if 4% is too much, this can be reduced to 1%).

Yes, we have tested on: MGI, PacBio, and Oxford Nanopore (ONT). Please note that our kits output Illumina-compatible kits. For MGI/BGI, conversion kits exist to make the libraries compatible with their platforms. For PacBio and ONT, their library prep kits should be used to prepare compatible libraries from cDNA obtained from our kits.

Yes, you can use PE100 for sequencing our products, except for VDJ, FocuSCOPE and sCircle libraries, where PE150 is required. However, to ensure a better quality of the alignment to the reference genome, we recommend to sequence PE150 with any of our products.

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