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市场调查报告书
商品编码
1863443
次世代定序(NGS) 资料储存市场按储存类型、部署类型、最终用户、定序平台和资料类型划分 - 全球预测,2025 年至 2032 年NGS Data Storage Market by Storage Type, Deployment Mode, End User, Sequencing Platform, Data Type - Global Forecast 2025-2032 |
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预计到 2032 年,次世代定序(NGS) 资料储存市场将成长至 82.1 亿美元,复合年增长率为 14.62%。
| 关键市场统计数据 | |
|---|---|
| 基准年 2024 | 27.5亿美元 |
| 预计年份:2025年 | 31.5亿美元 |
| 预测年份 2032 | 82.1亿美元 |
| 复合年增长率 (%) | 14.62% |
研究机构、临床实验室和製药研发部门定序活动的快速发展,使得重新思考基因组资料的储存、保护和存取方式变得迫切。通量和读取长度的提升,加上日益数据密集型的检测方法以及对数据保留和可追溯性日益严格的监管要求,使得存储从一种运营资源跃升为一项战略资产,能够影响实验设计、共同研究模式以及获得洞见所需的时间。忽视储存的机构将面临资料传输瓶颈、营运复杂性增加以及分析速度变慢等问题。
现代储存环境必须平衡以下相互衝突的需求:高效能存取以支援即时分析;经济高效的归檔以确保长期合规性和科学可重复性;强大的安全性以保护敏感的患者资料和专有资料;灵活的部署方法以支援分散式协作研究。云端原生架构、分层储存方法以及专用压缩和资料管理工具的演进正在重塑机构建立端到端定序流程的方式。因此,储存策略已成为实现可扩展、合规且经济永续的基因组学工作流程的核心。
本报告旨在检验影响定序资料储存和利用方式的技术趋势、政策转变和营运实务。以下章节将为领导者提供实用建议,帮助他们整合技术发展、采购考量和使用者需求,进而规划符合科学研究和商业目标的储存投资。
定序资料储存格局正经历变革性的转变,这主要得益于定序仪器、资料管理软体和部署模式的创新。仪器技术的发展趋势是不断提高吞吐量和读取长度,从而持续推动对可扩展存储和高频宽传输能力的需求;同时,智能分层、压缩和元资料驱动的编配等软体技术的进步,正在减少原始数据采集和下游分析之间的摩擦。这些技术正在融合,加速从单一的本地孤岛向融合边缘、核心和云端元素的更灵活的架构的过渡。
同时,云端生态系的成熟正在改变采购和营运模式。各组织机构越来越多地采用混合模式,将对延迟敏感的工作负载部署在靠近运算资源的位置,同时利用云端容量进行突发分析和长期归檔。这种混合模式使机构能够在不牺牲分析效能的前提下优化整体拥有成本。同时,对资料主权、隐私和跨境协作日益增长的关注,也促使企业做出更精细的部署选择,并加强对供应商的实质审查调查。
营运实务也在不断发展。资料管治架构、可重复的资料管线和标准化的资料格式正逐渐成为协作研究和临床应用的先决条件。因此,整合策略控制、溯源追踪和自动化功能的储存策略正日益普及。这些变革要求相关人员以前瞻性的观点存储,将其视为一个能够支持研究敏捷性和临床信心的适应性平台。
2025 年关税和贸易调整的实施,为依赖进口储存组件和设备的企业在采购週期、硬体筹资策略和供应商选择方面引入了新的变数。关税变化可能会增加某些硬体类别的相对成本,并改变供应商的经济效益,迫使采购团队重新评估整体生命週期成本、供应商多元化以及资本支出和服务模式之间的平衡。为此,许多企业正在加快考虑服务合约、託管储存产品以及以软体为中心的解决方案,这些方案将储存容量的成长与初始硬体采购脱钩。
关税也将影响供应商谈判和区域筹资策略。依赖单一供应商采购特定型号设备的企业正在重新考虑多供应商策略和本地分销合作伙伴,以降低供应链波动风险。这重新激发了人们对模组化架构的兴趣,这种架构允许使用来自不同供应商的组件进行增量扩展,从而减少对受关税影响的SKU的依赖。对软体和云端原生解决方案的影响更为微妙,但也依然显着。硬体成本上涨可能会促使买家偏好订阅模式、云端容量和分层储存策略,这些策略强调压缩和生命週期管理。
监管合规性和互通性问题进一步影响着应对关税带来的成本压力的措施。各机构必须确保成本优化措施不会损害资料完整性、来源或存取控制。因此,财务、采购和科研部门的领导层正在紧密合作,使采购与营运优先事项保持一致,并确保储存决策既体现了财政审慎,也保障了科学研究的连续性。
透过对储存类型、部署类型、最终用户、定序平台和资料类型进行細項分析,可以清楚地了解需求和容量走向。就储存类型而言,硬体部署仍然是需要本地效能和控制的组织的基础,但对于不具备内部系统工程能力的机构来说,咨询、整合、支援和维护等服务的重要性日益凸显。专注于资料压缩、资料管理和资料安全的软体层起到放大器的作用,无需全面更新硬体即可有效扩展现有基础设施的容量并对其进行有效管治。
部署模式的差异凸显了云端、混合和本地部署策略如何与组织优先顺序相契合。纯云端方案为习惯远端管治的团队提供弹性以及简化的供应商管理;混合模式则结合了本地部署的效能(用于处理活跃工作负载)和云端的可扩展性(用于归檔和突发运算)。私有云端方案在法规环境中提供更多控制权,而公共云端平台则支援快速扩展并与託管分析服务整合。
最终用户细分凸显了不同的需求:学术和研究机构,包括政府实验室和大学,优先考虑灵活性、协作性和开放标准。医疗服务提供者,例如医院和诊所,要求严格的隐私控制、审核以及与临床系统的整合。从小型生物技术公司到大型製药企业,各种规模的製药和生物技术公司都专注于高通量完整性、知识产权 (IP) 的监管链以及优化的工作流程,以加速药物发现。定序平台的选择也会影响储存特性。长读长定序系统(例如 Oxford Nanopore 和 PacBio)产生的檔案结构和存取模式与 Illumina 和 MGI 的短读长定序技术不同,这会影响压缩策略、索引结构和运算资源的配置。最后,资料类型细分区分了用于长期储存的归檔冷资料储存和磁带、用于二次分析的处理格式(例如 BAM 和 VCF)以及需要快速资料汇入流程和临时高效能储存的原始资料格式(例如 BCL 和 FASTQ)。了解这些部分如何交叉,可以创建客製化的架构,以满足各种用例的效能、合规性和成本目标。
区域趋势在製定储存策略方面发挥着至关重要的作用。美洲、欧洲、中东和非洲以及亚太地区各自拥有不同的法规环境、基础设施和资金筹措环境。在美洲,云端运算的成熟应用、生物技术领域强劲的私人投资以及先进的研究网络,都催生了对可扩展、高效且与分析和临床资讯学紧密整合的储存解决方案的强劲需求。北美机构通常优先考虑那些能够支援互通性、为协作计划快速输出资料以及快速扩展容量的服务协议。
欧洲、中东和非洲地区 (EMEA) 面临着复杂的资料主权要求和基础设施成熟度参差不齐的挑战。该地区的组织重视能够支援符合本地监管、严格隐私保护和多司法管辖区合规机制的供应商解决方案的部署模式。这促使他们倾向于采用可根据本地法规结构进行配置的混合架构和私有云端部署。此外,合作联盟和跨区域研究通常需要标准化的资料管理实践和资料溯源追踪。
亚太地区是一个充满活力的区域,拥有高成长市场、显着的定序能力扩张以及多元化的法规结构。快速发展的研究和临床基因组学计画推动了网路连接受限地区对本地部署设备的需求,以及网路基础设施完善地区对云端原生模式的需求。在全部区域,区域供应链、关税风险和本地供应商生态系统都会影响采购决策,因此,制定具有地理意识的采购和部署策略对于确保营运弹性至关重要。
定序资料储存领域的竞争格局涵盖了成熟的基础设施供应商、专业的储存软体供应商以及提供託管储存和整合服务的服务公司。硬体供应商在效能、能源效率和模组化方面竞争,而软体供应商则透过安全功能来脱颖而出,例如高级压缩演算法、元资料为中心的资料管理、静态和传输加密、基于角色的存取控制以及审核日誌记录。服务供应商透过提供咨询和系统整合服务,弥合原始容量与实际运作准备之间的差距,从而发挥日益重要的策略作用。
伙伴关係和生态系统策略是反覆出现的主题。系统整合商和云端服务供应商正与定序平台和生物资讯软体製造商合作,提供检验方案,以缩短部署时间并降低营运风险。供应商对互通性和基于标准的API持开放态度,加速了与流程编配工具和实验室资讯管理系统的集成,最终减少了终端用户的客製化工程工作量。采购团队在评估供应商时,不仅应考虑技术契合度,还应考虑其支援服务、临床认证流程以及在法规环境下的过往记录。
最后,厂商业界降低 IT 资源有限的组织采用新技术的门槛,提供託管容量、资料生命週期自动化和与使用模式相关的基于消费的定价模式,使科研团队能够专注于成果而不是基础设施管理。
产业领导者应采取务实且多管齐下的方法,使储存架构与科学研究目标、合规要求和财务限制相契合。首先,应建立清晰的管治和资料生命週期策略,明确资料保留期限、存取控制和溯源要求,确保储存决策以已记录的营运需求为指导,而非临时选择。同时,应进行架构审查,将定序工作流程对应到储存层级。优先考虑低延迟、高吞吐量的资源,用于即时资料撷取和进行初步分析,并将託管云端或物件储存用于储存中间处理资料。在监管和可重复性要求允许的情况下,部署经济高效的冷储存层或磁带以进行长期储存。
筹资策略应包括供应商多元化、采用规避关税风险的合约条款,以及评估基于服务的替代方案,将资本支出转化为营运支出。投资于具备压缩、索引和元资料驱动自动化功能的资料管理软体,以最大限度地提高有效容量并简化搜寻。加强IT、生物资讯学、法律和实验室营运部门之间的跨职能协作,以确保储存解决方案符合安全性、效能和合规性目标。
最后,试点混合模式,将运算和储存部署在对低延迟要求极高的区域,并利用云端的扩充性来应对高峰需求和灾害復原。利用试点结果建构更广泛部署的商业案例,并确保持续监控效能、成本和监管合规性,以便随着技术和政策的发展调整策略。
本研究整合了定性和定量数据,以全面了解数据储存排序。调查方法包括对资深储存架构师、生物资讯主管和采购负责人进行专家访谈,以了解实际操作情况和实施障碍。对长读长和短读长平台储存模式和文件类型的技术评估,为效能需求和分层策略的分析提供了基础。来自学术、临床和商业实验室的案例研究,为架构选择和操作权衡提供了实际检验。
资料收集包括对供应商产品文件的审查,以及对代表性储存软体、压缩工具和整合功能的实际评估。该研究优先收集可重复的证据,例如基准测试的摄取速度、相关文件类型的压缩效率以及已记录的合规性。分析框架着重于将储存功能与使用案例需求相匹配,进行与采购和海关风险相关的全生命週期风险评估,并分析区域监管影响和实施方案。
研究过程采用多源资讯来源三角验证法,以减少偏差并确保建议的可行性。专有资料和客户具体需求均已匿名化处理,以便在不洩漏机密资讯的前提下清晰展现决策流程。最终形成的调查方法兼具技术严谨性和实用性,能够为制定储存现代化计画的相关人员提供参考。
高通量定序的广泛应用、不断变化的监管要求以及供应链经济格局的转变,三者之间的协同作用已将储存从一项辅助功能提升为对科研和临床成果具有切实影响的战略领域。那些采用基于管治、分层架构和软体优化的、精心设计的分段式储存策略的机构,将更有能力维持科学研究效率、保护敏感资料并应对政策和成本压力。资讯科技、生物资讯学、采购和法务部门之间的策略协调至关重要,以确保储存选择能够提升长期营运韧性,而非仅仅追求短期便利。
在不同地区和最终用户群体中,本地部署、混合部署和云端部署方案之间的最佳平衡点会因效能需求、监管限制和连接实际情况而异。同样,资费和供应链趋势也凸显了灵活采购的价值,并强调了软体即服务 (SaaS) 模式的重要性,这种模式可以最大限度地降低资本成本波动带来的风险。最终,随着定序工作负载的不断扩展,那些将储存视为一种可管理、可演进的能力,并整合自动化、成熟的追踪和跨供应商互通性的组织,将能够更快地获得洞察,降低风险,并以更永续运作。
这个结论性观点强调了报告的核心前提:储存决策是策略选择,它直接影响发现的速度和临床应用,因此应该与支援它们的定序平台和分析流程一样,得到同样的管治和投资。
The NGS Data Storage Market is projected to grow by USD 8.21 billion at a CAGR of 14.62% by 2032.
| KEY MARKET STATISTICS | |
|---|---|
| Base Year [2024] | USD 2.75 billion |
| Estimated Year [2025] | USD 3.15 billion |
| Forecast Year [2032] | USD 8.21 billion |
| CAGR (%) | 14.62% |
The rapid expansion of sequencing activities across research institutions, clinical laboratories, and pharmaceutical R&D has created an urgent need to rethink how genomic data is stored, protected, and accessed. Advances in throughput and read length, combined with increasingly data-rich assays and regulatory demands for retention and traceability, have elevated storage from an operational commodity to a strategic asset that influences experimental design, collaboration models, and time-to-insight. Organizations that treat storage as an afterthought face bottlenecks in data transfer, rising operational complexity, and compromised analytical velocity.
Today's storage environment must reconcile competing imperatives: high-performance access for active analysis, cost-effective archiving for long-term regulatory and scientific reproducibility, robust security to safeguard sensitive patient and proprietary data, and flexible deployment to support distributed collaborations. The evolution of cloud-native architectures, tiered storage approaches, and specialized compression and data management tools is reshaping how institutions architect end-to-end sequencing pipelines. Consequently, storage strategy now plays a central role in enabling scalable, compliant, and economically sustainable genomic workflows.
This introduction frames the report's purpose: to examine technological dynamics, policy shifts, and operational practices that determine how sequencing-generated data is preserved and mobilized. By synthesizing technological developments, procurement considerations, and user needs, the following sections present actionable insights for leaders planning storage investments that align with scientific and commercial objectives.
The landscape for sequencing data storage is undergoing transformative shifts driven by innovations in sequencing instrumentation, data management software, and deployment paradigms. Instrumentation trends that increase throughput and read lengths create a persistent demand for scalable storage and high-bandwidth transfer capabilities, while software advancements such as intelligent tiering, compression, and metadata-driven orchestration reduce friction between raw data acquisition and downstream analytics. Together, these technological vectors are accelerating the shift from monolithic on-premises silos toward more fluid architectures that blend edge, core, and cloud elements.
Concurrently, the maturation of cloud ecosystems has altered procurement and operational models. Organizations are increasingly adopting hybrid approaches that keep latency-sensitive workloads close to compute resources while leveraging cloud capacity for burst analysis and long-term archiving. This hybrid posture allows institutions to optimize total cost of ownership without sacrificing analytical performance. At the same time, rising attention to data sovereignty, privacy, and cross-border collaboration is prompting more nuanced deployment choices and supplier due diligence processes.
Operational practices are also evolving. Data governance frameworks, reproducible pipelines, and standardized data formats have emerged as prerequisites for collaborative science and clinical translation. As a result, storage strategies that integrate policy controls, provenance tracking, and automation enjoy stronger adoption. These transformative shifts collectively demand that stakeholders adopt a forward-looking view of storage as an adaptable platform that underpins research agility and clinical reliability.
The introduction of tariffs and trade adjustments in 2025 has introduced new variables into procurement cycles, hardware sourcing strategies, and vendor selection for organizations reliant on imported storage components and appliances. Tariff changes increase the relative cost of certain hardware categories and may shift vendor economics, prompting procurement teams to revisit total lifecycle costs, supplier diversification, and the balance between capital expenditure and service-based models. In response, many organizations are accelerating explorations of service agreements, managed storage offerings, and software-centric solutions that decouple storage capacity growth from upfront hardware purchases.
Tariffs also influence supplier negotiations and regional sourcing strategies. Organizations that previously relied on single-source procurement for specific appliance models are reconsidering multi-vendor approaches and local distribution partners to mitigate supply-chain volatility. This has spurred renewed interest in modular architectures that allow incremental expansion using components from alternative suppliers, reducing dependency on tariff-affected SKUs. For software and cloud-native solutions, the impact is subtler but still material: increased hardware costs can shift buyer preferences toward subscription models, cloud capacity, and tiered retention strategies that emphasize compression and lifecycle policies.
Regulatory compliance and interoperability concerns further shape responses to tariff-driven cost pressures. Institutions must ensure that cost-optimization measures do not compromise data integrity, provenance, or access controls. As a result, finance, procurement, and scientific leadership are collaborating more closely to align sourcing with operational priorities, ensuring that storage decisions reflect both fiscal prudence and research continuity.
Analyzing segmentation across storage types, deployment modes, end users, sequencing platforms, and data types reveals distinct vectors of demand and capability. When storage type is considered, hardware adoption remains foundational for organizations requiring on-premises performance and control, while services encompassing consulting, integration, and support and maintenance are increasingly critical for institutions that lack in-house systems engineering capacity. Software layers focused on data compression, data management, and data security act as force multipliers, enabling existing infrastructure to deliver higher effective capacity and stronger governance without wholesale hardware replacement.
Deployment mode differentiation highlights how cloud, hybrid, and on-premises strategies map to institutional priorities. Pure cloud approaches provide elasticity and simplified vendor management for teams comfortable with remote governance, whereas hybrid models combine on-premises performance for active workloads with cloud scalability for archival and burst compute. Private cloud variants offer more control for regulated environments, while public cloud platforms enable rapid scaling and integration with managed analytics services.
End-user segmentation underscores varied requirements: academic and research institutes, including government research labs and universities, prioritize flexibility, collaboration, and open standards; healthcare providers such as hospitals and clinics demand stringent privacy controls, auditability, and integration with clinical systems; pharmaceutical and biotechnology companies, spanning biotech SMEs and large pharma, focus on high-throughput integrity, chain-of-custody for IP, and optimized workflows that accelerate drug discovery. Sequencing platform choice also drives storage characteristics: long read systems such as those from Oxford Nanopore and PacBio generate distinct file profiles and access patterns compared with short read technologies from Illumina and MGI, influencing compression strategies, index structures, and compute co-location. Finally, data type segmentation differentiates archived cold storage and tape for long-term retention from processed formats like BAM and VCF used for secondary analysis, and raw formats such as BCL and FASTQ that require rapid ingest pipelines and temporary high-performance storage. Understanding how these segments intersect enables tailored architectures that meet performance, compliance, and cost objectives across diverse use cases.
Regional dynamics play a decisive role in shaping storage strategies, with distinctive regulatory, infrastructure, and funding environments across the Americas, Europe, Middle East & Africa, and Asia-Pacific. In the Americas, mature cloud adoption, robust private investment in biotech, and advanced research networks create strong demand for scalable, high-performance storage solutions that integrate tightly with analytics and clinical informatics. North American institutions frequently prioritize interoperability, fast data egress for collaborative projects, and service agreements that support rapid capacity expansion.
The Europe, Middle East & Africa region faces a complex mosaic of data sovereignty requirements and heterogeneous infrastructure maturity. Organizations here place a premium on deployment models that support localized control, rigorous privacy safeguards, and vendor solutions that align with multijurisdictional compliance regimes. This drives preference for hybrid architectures and private cloud implementations that can be configured to local regulatory frameworks. Additionally, collaborative consortia and pan-regional research initiatives often necessitate standardized data management practices and provenance tracking.
Asia-Pacific presents a dynamic mix of high-growth markets, substantial sequencing capacity expansion, and varying regulatory frameworks. Rapidly expanding research and clinical genomics programs are increasing demand for both on-premises appliances in regions with constrained connectivity and cloud-native models in areas with robust network infrastructure. Across these regions, regional supply chains, tariff exposure, and local vendor ecosystems shape procurement decisions, making geographically informed sourcing and deployment strategies essential for resilient operations.
The competitive landscape for sequencing data storage encompasses established infrastructure vendors, specialized storage software providers, and service firms that offer managed storage and integration services. Hardware vendors compete on performance, energy efficiency, and modularity, while software suppliers differentiate through advanced compression algorithms, metadata-centric data management, and security features such as encryption at rest and in transit, role-based access controls, and audit logging. Service providers play an increasingly strategic role by delivering consulting and systems integration that bridge the gap between raw capacity and operational readiness.
Partnerships and ecosystem plays are a recurring theme: system integrators and cloud providers are collaborating with sequencing platform manufacturers and bioinformatics software makers to offer validated stacks that reduce time to deployment and operational risk. Vendor openness to interoperability and standards-based APIs accelerates integration with pipeline orchestration tools and laboratory information management systems, which in turn reduces bespoke engineering effort for end users. For procurement teams, vendor evaluation must balance technical fit with support capabilities, certification pathways for clinical use, and demonstrated experience in regulated environments.
Finally, innovation in the vendor community continues to lower barriers to adoption for organizations with limited IT resources by offering managed capacity, data lifecycle automation, and consumption-based pricing models that align cost with usage patterns, allowing science teams to focus on results rather than infrastructure management.
Industry leaders should adopt a pragmatic, multi-pronged approach that aligns storage architecture with scientific objectives, compliance needs, and financial constraints. Begin by establishing clear governance and data lifecycle policies that define retention periods, access controls, and provenance requirements so that storage decisions follow documented operational imperatives rather than ad hoc choices. Simultaneously, conduct an architecture review that maps sequencing workflows to storage tiers: prioritize low-latency, high-throughput resources for active raw-data ingest and primary analysis; designate managed cloud or object storage for intermediate processed data; and implement cost-efficient cold tiers or tape for long-term archival where regulatory and reproducibility needs permit.
Procurement strategies should include supplier diversification, contract terms that protect against tariff-driven volatility, and evaluation of service-based alternatives that transform capital expenses into operational expenditures. Invest in data management software that provides compression, indexing, and metadata-driven automation to maximize usable capacity and streamline retrieval. Strengthen cross-functional collaboration between IT, bioinformatics, legal, and laboratory operations to ensure that storage solutions meet security, performance, and compliance objectives.
Finally, pilot hybrid models that co-locate compute and storage where low latency is critical while leveraging cloud elasticity for peak demand and disaster recovery. Use pilot outcomes to build business cases for broader rollouts, and ensure continuous monitoring of performance, costs, and regulatory posture to adapt strategy as technologies and policies evolve.
This research synthesized qualitative and quantitative inputs to produce a comprehensive perspective on sequencing data storage. The methodology combined expert interviews with senior storage architects, bioinformatics leads, and procurement officers to capture operational realities and adoption barriers. Technical assessments of storage patterns and file profiles across long read and short read platforms informed analysis of performance requirements and tiering strategies. Case studies from academic, clinical, and commercial labs provided real-world validation of architecture choices and operational trade-offs.
Data collection included vendor product literature review and hands-on evaluation of representative storage software, compression tools, and integration capabilities. The research prioritized reproducible evidence such as benchmarked ingest rates, compression efficacy on relevant file types, and documented compliance features. Analytical frameworks focused on aligning storage capabilities with use-case requirements, assessing total lifecycle risks associated with procurement and tariff exposure, and mapping regional regulatory influences to deployment choices.
Throughout, findings were triangulated across multiple sources to reduce bias and ensure that recommendations reflect operational feasibility. Where proprietary data or client-specific concerns arose, anonymized examples were used to illustrate decision pathways without compromising confidentiality. The resulting methodology balances technical rigor with practical applicability for stakeholders planning storage modernization initiatives.
The confluence of high-throughput sequencing, evolving regulatory expectations, and shifting supply-chain economics has elevated storage from a background utility to a strategic domain that materially affects scientific and clinical outcomes. Organizations that adopt intentional, segment-aware storage strategies-grounded in governance, tiered architectures, and software-enabled optimization-will be better positioned to sustain research productivity, protect sensitive data, and respond to policy and cost pressures. Strategic alignment across IT, bioinformatics, procurement, and legal functions is essential to ensure storage choices serve long-term operational resilience rather than short-term convenience.
Across regions and end-user types, the optimal balance between on-premises, hybrid, and cloud approaches depends on performance needs, regulatory constraints, and connectivity realities. Likewise, tariff and supply-chain dynamics underscore the value of flexible procurement and an emphasis on software and service models that minimize exposure to capital cost fluctuations. Ultimately, the organizations that treat storage as a managed, evolving capability-incorporating automation, provenance tracking, and vendor interoperability-will unlock faster insights, reduce risk, and achieve more sustainable operations as sequencing workloads continue to scale.
This concluding perspective underscores the central premise of the report: storage decisions are strategic choices that directly influence the pace of discovery and the viability of clinical translation, and they deserve the same level of governance and investment as the sequencing platforms and analytics pipelines they support.