Genomics


Data analysis and results interpretation


Funds to keep running experiments


Hands-on time (FTE resource)


Contiguous assembly Data processing


Complexity


Sample/library preparation Data storage


Quality control


Run time on machine Reproducibility


Cluster generation Emulsion PCR


2.07


1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 MEAN Rating SCORE 1 to 5, where 1 = not limiting, and 5 = very limiting


© HTStec 2012 NGS bottlenecks


Figure 7: Factors influencing the decision to purchase new NGS instruments


Sequencing yield Read length Instrument cost Read accuracy Sequencing cost


Ability of instrument to use paired reads


Existing infrastructure Run time


Flexibility/ability to switch modes


(ie between minimising run time, and optimising cost per base)


Typical DNA input requirements Performance on AT-rich genomes Ability to rent (not purchase) sequencer Compatibility with FRT-seq or OS-seq


2.91 2.74 2.30


1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 MEAN Rating SCORE 1 to 5, where 1 = least influence, and 5 = greatest influence


© HTStec 2012 3.39


3.27 3.31 3.32


3.14 4.37 4.14 4.02 3.92 3.78


Funds to keep running experiments was rated by survey respondents the most limiting NGS bottle- neck. This was followed by data analysis and results interpretation, and then hands-on time (FTE resource) (Figure 6).


NGS purchasing factors


Sequencing cost was rated by respondents the most important factor determining NGS instrument pur- chase. This was closely followed by read accuracy, instrument cost, read length and then sequencing yield (Figure 7).


Figure 8: Respondents use of third generation sequencing technologies in a clinical setting


Currently using 9%


Not currently using (in 2012) or planning to use 56%


© HTStec 2012


Planning to use by 2014 35%


‘Third generation’ sequencing Only 9% of survey respondents are currently using third generation sequencing in a clinical setting, and 35% intend to do so by 2014 (Figure 8). Sequencing cost was rated by respondents the most attractive attribute of third generation sequencers relative to their next-generation coun- terparts. This was followed by ease of workflow and read length. For all attributes rated, the expec- tation is that third generation sequencers will be more attractive than their next-generation counter- parts (Figure 9).


High raw error rate was ranked by survey respondents as the most serious potential issue affecting data quality in third generation sequencers. This was followed by difficulty in sequencing long homopolymeric regions and reductions in average sub-read lengths in compari- son with quoted average read lengths. Coverage bias when sequencing AT-rich genomes was ranked the least serious potential issue (Figure 10).


32 Drug Discovery World Spring 2013


2.58 2.62


2.51 2.52


2.38 3.14 3.06


2.93 2.94 2.97


NGS applications


The three most widely investigated NGS applica- tions today (2012) were targeted resequencing, mRNA-seq and whole transcriptome sequencing (49%, 47% and 43% of respondents ran these applications respectively). The least-run NGS application today (2012) was CLIP-seq (run by only 8% of respondents) (Figure 4).


Cancer was the most common primary focus of for survey respondents’ NGS investigations. However, no single primary focus constituted more than one-fifth of all responses (Figure 5).


Figure 6: Current bottlenecks in NGS 3.83


3.50


units present (35%). Smaller proportions of respondents were able to access two sequencing units (13%), three units (7%), four units (3%), five units (1%), 6 to 10 units (1%), 15-20 units (1%), 25-50 units (1%) and >50 units (1%). The mean number of units per lab was 3.7 (Figure 3).


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