Create an ER diagram. This design as described does NOT require sub-types.

For the ER diagram clearly indicate primary keys, foreign keys and relationships, including cardinality (i.e. 1-to-many). Add key fields as needed. The database will store data about samples sequenced using Next-gen sequencing technology. Specifically, it will store data about samples and the sequencing runs.

As a little background, a sample can be genomic DNA (gDNA) or RNA (cDNA). Each sample is bound to a glass slide-like structure called a flow cell, and a flow cell is then sequenced on an instrument. A single flow cell can hold many samples, but a given flowcell can only be sequenced once (then its discarded). A sample can be sequenced multiple times on different flow cells. We usually refer to the sequencing of a particular flowcell on a specific instrument as a sequencing run. Attributes to store:

• sample description (name assigned by the client), i.e. sample_XYZ-1
• sample mean Q (Quality) score, i.e. 33.8; this will likely vary if sequenced again
• sample percent bases with Q greater than 30, i.e. 86.2; this will likely vary if sequenced again
• sample_type: will be gDNA, RNA or unknown
• date sample collected
• flow cell ID, i.e. C5Y9JACXX. (These names are assigned by the manufacturer and are unique)
• instrument serial number, i.e. SN334
• instrument model name, i.e. MiSeq, HiSeq2500
• number of clusters on flow cell (this is the number of DNA fragments; whole number, may be > 10⁹
• Number of clusters passing filter (usually ~90 % of number of clusters)
• instrument analysis software version (i.e. 1.18.61); this will be updated from time to time, we should know what version was in effect for each sequencing run.
• date sequencing run completed.
• sequencing OK (this is a Boolean (True or False) flag to indicate if the data for a particular sample, run on a particular flow cell, is ok to report; next-gen technology doesnt always give usable results)