Typical workflows

Sequencing analysis¶

For processing the .fast5 or .dat raw data files, check out the prepared jupyter notebook: Processing script ( Download).

A single config file centralizes all measurement parameters, including the file name, event-finding settings, and filtering criteria.

I-V curve analysis¶

For processing the I-V curve measurement, check out IV curve script ( Download).

Once the poreFlow Python environment is configured, download this notebook and load your data file (.dat) to begin processing.

Measurement inspection and processing in poreFlow Dashboard¶

Start the poreFlow dashboard in a terminal by simply running:

poreflow

A new tab will automatically appear in your browser.

A typical nanopore sequencing workflow¶

graph LR
    A[Measurement] -->|Preprocessing| B[Refined measurement]
    B -->|Event finding| C[Events]

poreFlow¶

graph TD;
    A@{ shape: cyl, label: "ONT File<br><tt>.fast5</tt>"}<-->|Read/write|D[File<br><tt>poreflow.File</tt>]
    C@{ shape: cyl, label: "UTube File<br><tt>.dat</tt>"}-->|Converted|A
    D-->|Read a channel|B[Measurement<br><tt>poreflow.RawDataFrame</tt>]
    D<-->|"Find events<br><tt>.find_events()</tt>"|E[Events<br><tt>poreflow.EventsDataFrame</tt>]
%%    E-->|Saved|D
%%    D-->|"Get events<br><tt>.get_events()</tt>"|Ex
    D<-->|"Find steps in events<br><tt>.find_steps()</tt>"|G[Steps<br><tt>poreflow.StepsDataFrame</tt>]
%%    G-->|Saved|D
    E-->F[Events with stats<br><tt>poreflow.EventsDataFrame</tt>]
    G-->F
    F-->|Filter using stats|H["Boolean Mask<br><tt>pandas.Series</tt>"]
    H-->|"Filter events<br><tt>.filter_events()</tt>"|D
    D-->|"Get event<br><tt>.get_event()</tt>"|I[Steps<br><tt>poreflow.EventDataFrame</tt>]