Among the 232 respondants, 61% of the researchers were in the data analysis phase of their study. Researchers indicated some of the major challenges they faced during the data analysis phase were:
- Moving the research data along the workflow
- Data analysis and construction
- Sharing data with collaborators
- Data storage
When asked what measures does the NGS industry need to take in terms on enhancing the quality and availability of their services, researchers indicated that the best approach would be through user-driven directives. While NGS data standardization seems to be the hot-topic among experts in the field of biomedical research, it is evident that the biotechnology and pharma industry seems to be well aligned with these goals too. Approximately, one-third of the participants seemed to indicate that lack of industry standards is one of the main reasons for possible failure of projects using NGS technologies.
Among the most commonly used NGS platforms were Illumina, Life Technologies, Roche/454 and PacBio. Over 64% of participants indicated a keen interest in applying cloud technologies for NGS data analysis, storage, and sharing. But when asked about some of the challenges they face in terms of implementing cloud-based technology in their research, cost and security were two of the major limiting factors.
There are a number of NGS data-analysis software in the market that provide great features like genomic data visualization and accelerated data analysis combined with cost-effective, collaborative cloud based technology. However nearly 70% of the participants opt for open-source NGS data-analysis software.
Based on this survey, we can see that while the commercial NGS industry has been taken over by open-source NGS data-analysis software that are widely used by the biotechnology and pharma industry, there is still a lot of work that needs to be done in providing a secure and more cost-effective NGS solution for researchers.