QIAGEN Digital Insights Customer Research
Which of the following do you consider the biggest gap in the toolset of MGM?
QIAGEN Digital Insights Customer Research
When you have identified a pathway from a metagenomic functional profiling analysis, which steps do you typically perform subsequently?
| Identification of central nodes/enzymes as drug targets |
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| Identification of the phenotypic consequences of differential abundance/expression |
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| Identification of harmful/beneficial metabolites |
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| Other |
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QIAGEN Digital Insights Customer Research
Which databases for metagenomic profiling do you use most frequently?
| Kraken databases |
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| OTU databases, e.g. SILVA, Greengenes ... |
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| ProGenomes |
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| Custom-built with CLC |
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| Custom-built outside of CLC |
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| Pre-built databases in CLC (Optimized databases from Download Microbial Reference database) |
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| Other |
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QIAGEN Digital Insights Customer Research
Which functional metagenomic analysis strategies do you use in your research?
| Amplicon based (e.g. 16S, 18S ITS ...) sequencing and functional inference - e.g. PiCRUSt, Tax4Fun, Piphillin ... |
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| Whole metagenomic DNA sequencing and functional inference from read mappings to assemblies/genomes |
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| Whole metatranscriptomics (metagenomic RNA-Seq) sequencing |
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| Metagenomic single-cell RNA sequencing |
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| Other |
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QIAGEN Digital Insights Customer Research
For comparative metagenomics or functional metagenomics, which resources do you typically use?
| Manually search SRA for relevant datasets and analyze them from scratch |
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| Manually search SRA for relevant datasets and use the results from relevant publications |
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| Search the web for relevant publications |
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| MGnify (https://www.ebi.ac.uk/metagenomics/) |
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| HMP (https://www.hmpdacc.org/) |
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| Use an internal data collection and comparison |
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| Other |
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QIAGEN Customer Research
What is the ideal length of time you would like to store stool or soil samples at each temperature, provided that the quality remained the same?
| Up to 24 hours | 24 - 72 hours | 72 hours - 1 week | 1 week-1 month | More than 1 month | |
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| Room temp (15-25C) |
27% |
8% |
24% |
19% |
22% |
| 4C |
8% |
5% |
8% |
34% |
45% |
| >35C |
25% |
15% |
0% |
15% |
45% |
QIAGEN Customer Research
How much would you be willing to pay for a collection device with stabilizing solution compared to just a bulk stabilizing solution?
| 10% more for collection device vs. bulk |
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| 20% more for collection device vs. bulk |
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| 50% more for collection device vs. bulk |
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| I would not use a bulk stabilization solution |
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| Other |
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QIAGEN Customer Research
Using your current stool stabilization solution, do you face any of the following challenges?
| The cost of the collection device/stabilization solution is too high |
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| DNA is degraded following storage |
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| RNA is degraded following storage |
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| Results of sequencing after storage differ from those of fresh samples |
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| I want to store stool samples at higher temperatures than recommended |
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| I want to store stool samples for longer than recommended |
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| None of the above |
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What bottlenecks did deploying Ingenuity Variant Analysis solve for your laboratory or organization?
| Workflow bottleneck due to the hours of data analysis and review required by other software products |
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| Delayed publication due to a lack of confidence in research findings |
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| Inability to identify the highest value variants resulting in extended experimental timelines and costs |
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| High IT infrastructure costs |
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Which of the following benefits have you noticed since you began using the Ingenuity Variant Analysis plugin for Ion Reporter?
| Helps reduce time to generate a short list of interesting variants |
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| Increases access to rich biological content |
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| Increases efficiency and team productivity |
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| Enables improved sharing and collaboration |
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| Other |
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What were the top drivers for selecting IPA for RNA seq analysis?
| Quickly identify differentially expressed isoforms |
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| Interpret the impact of expression changes in the context of biological processes, disease and cellular phenotypes, and molecular interactions |
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| Visualize your RNA seq data in the context of Isoform View |
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| Compile targeted bibliographies with experimental evidence linking your differentially expressed isoforms to biological processes, disease, and molecular interactions |
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| Other |
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Rate the following IPA capabilities in terms of how differentiated they are compared to the competition.
Extremely Differentiated
Highly Differentiated
Differentiated
Not Differentiated
| Faster time to insights |
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| Ease of use |
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| Novel insights |
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| Deeper analysis |
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What were the top drivers for selecting IPA for RNA seq analysis?
| Quickly identify differentially expressed isoforms |
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| Interpret the impact of expression changes in the context of biological processes, disease and cellular phenotypes, and molecular interactions |
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| Visualize your RNA seq data in the context of Isoform View |
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| Compile targeted bibliographies with experimental evidence linking your differentially expressed isoforms to biological processes, disease, and molecular interactions |
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What were the top drivers for selecting IPA for RNA seq analysis?
| Quickly identify differentially expressed isoforms |
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| Interpret the impact of expression changes in the context of biological processes, disease and cellular phenotypes, and molecular interactions |
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| Visualize your RNA seq data in the context of Isoform View |
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| Compile targeted bibliographies with experimental evidence linking your differentially expressed isoforms to biological processes, disease, and molecular interactions |
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| Other |
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What types of challenges did deploying IPA for RNA sequencing analysis solve for your laboratory?
| Understanding the structure of different isoforms |
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| More precise measurement of transcripts |
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| Ability to distinguish different isoforms |
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| Identifying biologically relevant isoforms |
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| Other |
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What were the top drivers for selecting IPA for RNA seq analysis?
| Quickly identify differentially expressed isoforms |
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| Interpret the impact of expression changes in the context of biological processes, disease and cellular phenotypes, and molecular interactions |
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| Visualize your RNA seq data in the context of Isoform View |
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| Compile targeted bibliographies with experimental evidence linking your differentially expressed isoforms to biological processes, disease, and molecular interactions |
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| Other |
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