pod5 0.3.10

Oxford Nanopore Technologies Pod5 File Format Python API and Tools

POD5 Python Package

The pod5 Python package contains the tools and python API wrapping the compiled bindings for the POD5 file format from lib_pod5.

Installation

The pod5 package is available on pypi and is installed using pip:

  > pip install pod5

Usage

Reading a POD5 File

To read a pod5 file provide the the Reader class with the input pod5 file path and call Reader.reads() to iterate over read records in the file. The example below prints the read_id of every record in the input pod5 file.

import pod5 as p5

with p5.Reader("example.pod5") as reader:
    for read_record in reader.reads():
        print(read_record.read_id)

To iterate over a selection of read_ids supply Reader.reads() with a collection of read_ids which must be UUID compatible:

import pod5 as p5

# Create a collection of read_id UUIDs
read_ids: List[str] = [
  "00445e58-3c58-4050-bacf-3411bb716cc3",
  "00520473-4d3d-486b-86b5-f031c59f6591",
]

with p5.Reader("example.pod5") as reader:
    for read_record in reader.reads(selection=read_ids):
        assert str(read_record.read_id) in read_ids

Plotting Signal Data Example

Here is an example of how a user may plot a read’s signal data against time.

import matplotlib.pyplot as plt
import numpy as np

import pod5 as p5

# Using the example pod5 file provided
example_pod5 = "test_data/multi_fast5_zip.pod5"
selected_read_id = '0000173c-bf67-44e7-9a9c-1ad0bc728e74'

with p5.Reader(example_pod5) as reader:

    # Read the selected read from the pod5 file
    # next() is required here as Reader.reads() returns a Generator
    read = next(reader.reads(selection=[selected_read_id]))

    # Get the signal data and sample rate
    sample_rate = read.run_info.sample_rate
    signal = read.signal

    # Compute the time steps over the sampling period
    time = np.arange(len(signal)) / sample_rate

    # Plot using matplotlib
    plt.plot(time, signal)

Writing a POD5 File

The pod5 package provides the functionality to write POD5 files.

It is strongly recommended that users first look at the available tools when manipulating existing datasets, as there may already be a tool to meet your needs. New tools may be added to support our users and if you have a suggestion for a new tool or feature please submit a request on the pod5-file-format GitHub issues page.

Below is an example of how one may add reads to a new POD5 file using the Writer and its add_read() method.

import pod5 as p5

# Populate container classes for read metadata
pore = p5.Pore(channel=123, well=3, pore_type="pore_type")
calibration = p5.Calibration(offset=0.1, scale=1.1)
end_reason = p5.EndReason(name=p5.EndReasonEnum.SIGNAL_POSITIVE, forced=False)
run_info = p5.RunInfo(
    acquisition_id = ...
    acquisition_start_time = ...
    adc_max = ...
    ...
)
signal = ... # some signal data as numpy np.int16 array

read = p5.Read(
    read_id=UUID("0000173c-bf67-44e7-9a9c-1ad0bc728e74"),
    end_reason=end_reason,
    calibration=calibration,
    pore=pore,
    run_info=run_info,
    ...
    signal=signal,
)

with p5.Writer("example.pod5") as writer:
    # Write the read object
    writer.add_read(read)

Tools

1. pod5 view
2. pod5 inspect
3. pod5 merge
4. pod5 filter
5. pod5 subset
6. pod5 repack
7. pod5 recover
8. pod5 convert fast5
9. pod5 convert to_fast5
10. pod5 update

The pod5 package provides the following tools for inspecting and manipulating POD5 files as well as converting between .pod5 and .fast5 file formats.

To disable the tqdm <https://github.com/tqdm/tqdm>_ progress bar set the environment variable POD5_PBAR=0.

To enable debugging output which may also output detailed log files, set the environment variable POD5_DEBUG=1

Pod5 View

The pod5 view tool is used to produce a table similarr to a sequencing summary from the contents of .pod5 files. The default output is a tab-separated table written to stdout with all available fields.

This tools is indented to replace pod5 inspect reads and is over 200x faster.

> pod5 view --help

# View the list of fields with a short description in-order (shortcut -L)
> pod5 view --list-fields

# Write the summary to stdout
> pod5 view input.pod5

# Write the summary of multiple pod5s to a file
> pod5 view *.pod5 --output summary.tsv

# Write the summary as a csv
> pod5 view *.pod5 --output summary.csv --separator ','

# Write only the read_ids with no header (shorthand -IH)
> pod5 view input.pod5 --ids --no-header

# Write only the listed fields
# Note: The field order is fixed the order shown in --list-fields
> pod5 view input.pod5 --include "read_id, channel, num_samples, end_reason"

# Exclude some unwanted fields
> pod5 view input.pod5 --exclude "filename, pore_type"

Pod5 inspect

The pod5 inspect tool can be used to extract details and summaries of the contents of .pod5 files. There are two programs for users within pod5 inspect and these are read and reads

> pod5 inspect --help
> pod5 inspect {reads, read, summary} --help

Pod5 inspect reads

:warning: This tool is deprecated and has been replaced by pod5 view which is significantly faster.

Inspect all reads and print a csv table of the details of all reads in the given .pod5 files.

> pod5 inspect reads pod5_file.pod5

  read_id,channel,well,pore_type,read_number,start_sample,end_reason,median_before,calibration_offset,calibration_scale,sample_count,byte_count,signal_compression_ratio
  00445e58-3c58-4050-bacf-3411bb716cc3,908,1,not_set,100776,374223800,signal_positive,205.3,-240.0,0.1,65582,58623,0.447
  00520473-4d3d-486b-86b5-f031c59f6591,220,1,not_set,7936,16135986,signal_positive,192.0,-233.0,0.1,167769,146495,0.437
    ...

Pod5 inspect read

Inspect the pod5 file, find a specific read and print its details.

> pod5 inspect read pod5_file.pod5 00445e58-3c58-4050-bacf-3411bb716cc3

  File: out-tmp/output.pod5
  read_id: 0e5d6827-45f6-462c-9f6b-21540eef4426
  read_number:    129227
  start_sample:   367096601
  median_before:  171.889404296875
  channel data:
  channel: 2366
  well: 1
  pore_type: not_set
  end reason:
  name: signal_positive
  forced False
  calibration:
  offset: -243.0
  scale: 0.1462070643901825
  samples:
  sample_count: 81040
  byte_count: 71989
  compression ratio: 0.444
  run info
      acquisition_id: 2ca00715f2e6d8455e5174cd20daa4c38f95fae2
      acquisition_start_time: 2021-07-23 13:48:59.780000
      adc_max: 0
      adc_min: 0
      context_tags
      barcoding_enabled: 0
      basecall_config_filename: dna_r10.3_450bps_hac_prom.cfg
      experiment_duration_set: 2880
      ...

Pod5 merge

pod5 merge is a tool for merging multiple .pod5 files into one monolithic pod5 file.

The contents of the input files are checked for duplicate read_ids to avoid accidentally merging identical reads. To override this check set the argument -D / --duplicate-ok

# View help
> pod5 merge --help

# Merge a pair of pod5 files
> pod5 merge example_1.pod5 example_2.pod5 --output merged.pod5

# Merge a glob of pod5 files
> pod5 merge *.pod5 -o merged.pod5

# Merge a glob of pod5 files ignoring duplicate read ids
> pod5 merge *.pod5 -o merged.pod5 --duplicate-ok

Pod5 filter

pod5 filter is a simpler alternative to pod5 subset where reads are subset from one or more input .pod5 files using a list of read ids provided using the --ids argument and writing those reads to a single --output file.

See pod5 subset for more advanced subsetting.

> pod5 filter example.pod5 --output filtered.pod5 --ids read_ids.txt

The --ids selection text file must be a simple list of valid UUID read_ids with one read_id per line. Only records which match the UUID regex (lower-case) are used. Lines beginning with a # (hash / pound symbol) are interpreted as comments. Empty lines are not valid and may cause errors during parsing.

The filter and subset tools will assert that any requested read_ids are present in the inputs. If a requested read_id is missing from the inputs then the tool will issue the following error:

POD5 has encountered an error: 'Missing read_ids from inputs but --missing-ok not set'

To disable this warning then the '-M / --missing-ok' argument.

When supplying multiple input files to 'filter' or 'subset', the tools is effectively performing a merge operation. The 'merge' tool is better suited for handling very large numbers of input files.

Example filtering pipeline

This is a trivial example of how to select a random sample of 1000 read_ids from a pod5 file using pod5 view and pod5 filter.

# Get a random selection of read_ids
> pod5 view all.pod5 --ids --no-header --output all_ids.txt
> all_ids.txt sort --random-sort | head --lines 1000 > 1k_ids.txt

# Filter to that selection
> pod5 filter all.pod5 --ids 1k_ids.txt --output 1k.pod5

# Check the output
> pod5 view 1k.pod5 -IH | wc -l
1000

Pod5 subset

pod5 subset is a tool for subsetting reads in .pod5 files into one or more output .pod5 files. See also pod5 filter

The pod5 subset tool requires a mapping which defines which read_ids should be written to which output. There are multiple ways of specifying this mapping which are defined in either a .csv file or by using a --table (csv or tsv) and instructions on how to interpret it.

pod5 subset aims to be a generic tool to subset from multiple inputs to multiple outputs. If your use-case is to filter read_ids from one or more inputs into a single output then pod5 filter might be a more appropriate tool as the only input is a list of read_ids.

# View help
> pod5 subset --help

# Subset input(s) using a pre-defined mapping
> pod5 subset example_1.pod5 --csv mapping.csv

# Subset input(s) using a dynamic mapping created at runtime
> pod5 subset example_1.pod5 --table table.txt --columns barcode

Care should be taken to ensure that when providing multiple input .pod5 files to pod5 subset that there are no read_id UUID clashes. If a duplicate read_id is detected an exception will be raised unless the --duplicate-ok argument is set. If --duplicate-ok is set then both reads will be written to the output, although this is not recommended.

Note on positional arguments

The --columns argument will greedily consume values and as such, care should be taken with the placement of any positional arguments. The following line will result in an error as the input pod5 file is consumed by --columns resulting in no input file being set.

# Invalid placement of positional argument example.pod5
$ pod5 subset --table table.txt --columns barcode example.pod5

Creating a Subset Mapping

Target Mapping (.csv)

The example below shows a .csv subset target mapping. Any lines (e.g. header line) which do not have a read_id which matches the UUID regex (lower-case) in the second column is ignored.

target, read_id
output_1.pod5,132b582c-56e8-4d46-9e3d-48a275646d3a
output_1.pod5,12a4d6b1-da6e-4136-8bb3-1470ef27e311
output_2.pod5,0ff4dc01-5fa4-4260-b54e-1d8716c7f225
output_2.pod5,0e359c40-296d-4edc-8f4a-cca135310ab2
output_2.pod5,0e9aa0f8-99ad-40b3-828a-45adbb4fd30c

Target Mapping from Table

pod5 subset can dynamically generate output targets and collect associated reads based on a text file containing a table (csv or tsv) parsible by polars. This table file could be the output from pod5 view or from a sequencing summary. The table must contain a header row and a series of columns on which to group unique collections of values. Internally this process uses the polars.Dataframe.group_by <https://pola-rs.github.io/polars/py-polars/html/reference/dataframe/api/polars.DataFrame.group_by.html>_ function where the by parameter is the sequence of column names specified with the --columns argument.

Given the following example --table file, observe the resultant outputs given various arguments:

read_id    mux    barcode      length
read_a     1      barcode_a    4321
read_b     1      barcode_b    1000
read_c     2      barcode_b    1200
read_d     2      barcode_c    1234

> pod5 subset example_1.pod5 --output barcode_subset --table table.txt --columns barcode
> ls barcode_subset
barcode-barcode_a.pod5     # Contains: read_a
barcode-barcode_b.pod5     # Contains: read_b, read_c
barcode-barcode_c.pod5     # Contains: read_d

> pod5 subset example_1.pod5 --output mux_subset --table table.txt --columns mux
> ls mux_subset
mux-1.pod5     # Contains: read_a, read_b
mus-2.pod5     # Contains: read_c, read_d

> pod5 subset example_1.pod5 --output barcode_mux_subset --table table.txt --columns barcode mux
> ls barcode_mux_subset
barcode-barcode_a_mux-1.pod5    # Contains: read_a
barcode-barcode_b_mux-1.pod5    # Contains: read_b
barcode-barcode_b_mux-2.pod5    # Contains: read_c
barcode-barcode_c_mux-2.pod5    # Contains: read_d

Output Filename Templating

When subsetting using a table the output filename is generated from a template string. The automatically generated template is the sequential concatenation of column_name-column_value followed by the .pod5 file extension.

The user can set their own filename template using the --template argument. This argument accepts a string in the Python f-string style <https://docs.python.org/3/tutorial/inputoutput.html#formatted-string-literals>_ where the subsetting variables are used for keyword placeholder substitution. Keywords should be placed within curly-braces. For example:

# default template used = "barcode-{barcode}.pod5"
> pod5 subset example_1.pod5 --output barcode_subset --table table.txt --columns barcode

# default template used = "barcode-{barcode}_mux-{mux}.pod5"
> pod5 subset example_1.pod5 --output barcode_mux_subset --table table.txt --columns barcode mux

> pod5 subset example_1.pod5 --output barcode_subset --table table.txt --columns barcode --template "{barcode}.subset.pod5"
> ls barcode_subset
barcode_a.subset.pod5    # Contains: read_a
barcode_b.subset.pod5    # Contains: read_b, read_c
barcode_c.subset.pod5    # Contains: read_d

Example subsetting from pod5 inspect reads

The pod5 inspect reads tool will output a csv table summarising the content of the specified .pod5 file which can be used for subsetting. The example below shows how to split a .pod5 file by the well field.

# Create the csv table from inspect reads
> pod5 inspect reads example.pod5 > table.csv
> pod5 subset example.pod5 --table table.csv --columns well

Pod5 repack

pod5 repack will simply repack .pod5 files into one-for-one output files of the same name.

> pod5 repack pod5s/*.pod5 repacked_pods/

Pod5 Recover

pod5 recover will attempt to recover data from corrupted or truncated .pod5 files by copying all valid table batches and cleanly closing the new files. New files are written as siblings to the inputs with the _recovered.pod5 suffix.

> pod5 recover --help
> pod5 recover broken.pod5
> ls
broken.pod5 broken_recovered.pod5

pod5 convert fast5

The pod5 convert fast5 tool takes one or more .fast5 files and converts them to one or more .pod5 files.

If the tool detects single-read fast5 files, please convert them into multi-read fast5 files using the tools available in the ont_fast5_api project.

The progress bar shown during conversion assumes the number of reads in an input .fast5 is 4000. The progress bar will update the total value during runtime if required.

Some content previously stored in .fast5 files is not compatible with the POD5 format and will not be converted. This includes all analyses stored in the .fast5 file.

Please ensure that any other data is recovered from .fast5 before deletion.

By default pod5 convert fast5 will show exceptions raised during conversion as warnings to the user. This is to gracefully handle potentially corrupt input files or other runtime errors in long-running conversion tasks. The --strict argument allows users to opt-in to strict runtime assertions where any exception raised will promptly stop the conversion process with an error.

# View help
> pod5 convert fast5 --help

# Convert fast5 files into a monolithic output file
> pod5 convert fast5 ./input/*.fast5 --output converted.pod5

# Convert fast5 files into a monolithic output in an existing directory
> pod5 convert fast5 ./input/*.fast5 --output outputs/
> ls outputs/
output.pod5 # default name

# Convert each fast5 to its relative converted output. The output files are written
# into the output directory at paths relatve to the path given to the
# --one-to-one argument. Note: This path must be a relative parent to all
# input paths.
> ls input/*.fast5
file_1.fast5 file_2.fast5 ... file_N.fast5
> pod5 convert fast5 ./input/*.fast5 --output output_pod5s/ --one-to-one ./input/
> ls output_pod5s/
file_1.pod5 file_2.pod5 ... file_N.pod5

# Note the different --one-to-one path which is now the current working directory.
# The new sub-directory output_pod5/input is created.
> pod5 convert fast5 ./input/*.fast5 output_pod5s --one-to-one ./
> ls output_pod5s/
input/file_1.pod5 input/file_2.pod5 ... input/file_N.pod5

# Convert all inputs so that they have neibouring pod5 in current directory
> pod5 convert fast5 *.fast5 --output . --one-to-one .
> ls
file_1.fast5 file_1.pod5 file_2.fast5 file_2.pod5  ... file_N.fast5 file_N.pod5

# Convert all inputs so that they have neibouring pod5 files from a parent directory
> pod5 convert fast5 ./input/*.fast5 --output ./input/ --one-to-one ./input/
> ls input/*
file_1.fast5 file_1.pod5 file_2.fast5 file_2.pod5  ... file_N.fast5 file_N.pod5

Pod5 convert to_fast5

The pod5 convert to_fast5 tool takes one or more .pod5 files and converts them to multiple .fast5 files. The default behaviour is to write 4000 reads per output file but this can be controlled with the --file-read-count argument.

# View help
> pod5 convert to_fast5 --help

# Convert pod5 files to fast5 files with default 4000 reads per file
> pod5 convert to_fast5 example.pod5 --output pod5_to_fast5/
> ls pod5_to_fast5/
output_1.fast5 output_2.fast5 ... output_N.fast5

Pod5 Update

The pod5 update tools is used to update old pod5 files to use the latest schema. Currently the latest schema version is version 3.

Files are written into the --output directory with the same name.

> pod5 update --help

# Update a named files
> pod5 update my.pod5 --output updated/
> ls updated
updated/my.pod5

# Update an entire directory
> pod5 update old/ -o updated/