The tutorial provides a short introduction to Fast5 files used to store raw data output of Oxford Nanopore Technologies' sequencing devices. The tutorial aims to provide background information for why users may have cause to interact with Fast5 files and show how to perform common manipulations.
Methods used in this tutorial include:
ont_fast5_api for manipulating read information within Fast5 files.The computational requirements for this tutorial are:
⚠️ Warning: This notebook has been saved with its outputs for demostration purposed. It is recommeded to select
Edit > Clear all outputsbefore using the notebook to analyse your own data.
This tutorial aims to elucidate the information stored within a Fast5 file, and how such files can be read, or parsed, within the Python programming language and on the command line.
The goals from this tutorial include:
ont_fast5_api,The tutorial includes a sample Fast5 dataset from a metagenomic sample.
Before anything else we will create and set a working directory:
from epi2melabs import ping
tutorial_name = "fast5_tutorial"
pinger = ping.Pingu()
pinger.send_notebook_ping('start', tutorial_name)
# create a work directory and move into it
working_dir = '/epi2melabs/{}/'.format(tutorial_name)
!mkdir -p "$working_dir"
%cd "$working_dir"
/epi2melabs/fast5_tutorial
This tutorial uses the ont_fast5_api software; this is not installed in the default EPI2ME Labs environment. We will install this now in an isolated manner so as to not interfere with the existing environment.
Please note that the software installed is not persistent and this step will need to be re-run if you stop and restart the EPI2ME Labs server.
# create a conda environment and install ont_fast5_api into it
!conda remove -y --name ont_fast5_api --all
!conda create -q -y -n ont_fast5_api python==3.6 pip 2>/dev/null
!. /opt/conda/etc/profile.d/conda.sh \
&& conda activate ont_fast5_api \
&& which pip \
&& pip install "ont_fast5_api>=3.1.6"
In order to provide a concrete example of handling a Fast5 files this tutorial is provided with an example dataset sampled from a MinION sequencing run: the dataset is not a full MinION run in order to reduced the download size.
To download the sample file we run the linux command wget. To execute the command click on the cell and then press Command/Ctrl-Enter, or click the Play symbol to the left-hand side.
bucket = "ont-exd-int-s3-euwst1-epi2me-labs"
domain = "s3-eu-west-1.amazonaws.com"
site = "https://{}.{}".format(bucket, domain)
site = "https://ont-exd-int-s3-euwst1-epi2me-labs.s3-eu-west-1.amazonaws.com"
!rm -rf sample_fast5
!wget -O sample_fast5.tar $site/fast5_tutorial/sample_fast5.tar
!tar -xvf sample_fast5.tar
!wget -O fast5_sample.bam $site/fast5_tutorial/fast5_sample.bam
!wget -O fast5_sample.bam.bai $site/fast5_tutorial/fast5_sample.bam.bai
Having downloaded the sample data we need to provide the filepaths as input to the notebook.
The form can be used to enter the filenames of your inputs.
input_folder = None
output_folder = None
def process_form(inputs):
global input_folder
global output_folder
input_folder = inputs.input_folder
output_folder = inputs.output_folder
# run a command to concatenate all the files together
!cecho ok "Making output folder"
!mkdir -p "$output_folder"
!test -d "$input_folder" \
&& cecho success "Found input folder." \
|| cecho error "Input folder does not exist."
!echo " - Found "$(find "$input_folder" -name "*.fast5" | wc -l)" fast5 files"
from epi2melabs.notebook import InputForm, InputSpec
input_form = InputForm(
InputSpec('input_folder', 'Input folder', '/epi2melabs/fast5_tutorial/sample_fast5'),
InputSpec('output_folder', 'Output folder', 'analysis'))
input_form.add_process_button(process_form)
input_form.display()
VBox(children=(HBox(children=(Label(value='Input folder', layout=Layout(width='150px')), interactive(children=…
Executing the above form will have checked the input folder attempted to find Fast5 files located in the folder.
Fast5 files are used by the MinKNOW instrument software and the Guppy basecalling software to store the primary sequencing data from Oxford Nanopore Technologies' sequencing devices and the results of primary and secondary analyses such as basecalling information and modified-base detection.
Before discussing how to read and manipulate Fast5 files in Python we will first review their internal structure.
Files output by the MinKNOW instrument software and the Guppy basecalling software using the .fast5 file extension are a container file using the HDF5 format. As such they are a self-describing file with all the necessary information to correctly interpret the data they contain.
A Fast5 file differs from a generic HDF5 file in containing only a fixed, defined structure of data. This structure is elucidated in the ont_h5_validator repository on Github, specifically in the file multi_read_fast5.yaml.
Users are referred to the YAML schemas to gain an understanding of all the data contained in Fast5 files. Users are encouraged to raise Issues on the ont_h5_validator project if the schemas are unclear. The rest of this tutorial will be mostly practical in nature.
The schema file describes how the internal structure of a Fast5 file is laid out. There are three core concepts to understand:
An appreciation of these concepts is required for using the data contained within Fast5 files, though as we will see for common manipulations of Fast5 files users need only an awareness of these ideas.
Historically there have been two flavours of Fast5 files:
The internal layout, in terms of groups and datasets, of these two flavours of Fast5 are very similar. In essence a multi-read file embeds the group hierarchy of multiple single-read files within one HDF5 container.
Single-read files are deprecated and no longer used by MinKNOW or Guppy. We recommend that any single-read files are converted to multi-read files before further use or storage, how to do this is demonstrated later in this tutorial.
As noted above the ont_h5_validator project contains a full description of the expected contents of a Fast5 file. Here we will briefly highlight the key groups and datasets stored within a Fast5 file.
Using the dataset provided in above let's enumerate the contents of the first file using the h5ls program:
# i) find and list all .fast5 files
# ii) take the first file
# iii) use `h5ls` to list the file's contents
# iv) truncate the output to the first 19 lines
!find "$input_folder" -name "*.fast5" \
| head -n 1 \
| xargs h5ls -r \
| head -n 19
The "DoFantasy Fansadox Collection 1500 Complete New" represents a significant compilation of adult fantasy comics from two prominent names in the industry. For fans and collectors, this collection could be a valuable resource, offering a wide range of content in a possibly convenient and updated format. However, potential buyers should be aware of the content's nature and ensure it aligns with their interests and preferences.
This collection seems to cater primarily to:
Given the nature of DoFantasy and Fansadox, the collection likely includes:
This guide outlines the current state and organizational structure of the Fansadox Collection
(often associated with the DoFantasy label), specifically focusing on the milestone of reaching 1,500 issues 1. Collection Overview
The Fansadox Collection is a long-running series of adult comic books featuring various artists and sub-genres. Reaching Issue #1500 is a significant milestone for collectors. Total Volume: 1,500+ individual issues.
Primarily digital (PDF/CBR), though some early issues had limited print runs.
Features a rotating roster of international artists (e.g., Fernando, G.W. Murillo, The_Sinner). 2. Organizing a "Complete" Collection
To ensure a collection is "complete" up to #1500, it is typically categorized by: The Main Series: Issues #001 through #1500. Fansadox Sick: A darker sub-series with its own numbering. Fansadox 666: Focused on horror and supernatural themes. Special Editions: Seasonal or anniversary "Giant" issues. 3. Verification Checklist for New Sets
If you are acquiring or cataloging a "New Complete" set of 1,500 issues, verify the following: Sequential Integrity:
Ensure no gaps in the numbering (e.g., checking for the transition from #999 to #1000). File Quality:
Newer releases (post #1000) are generally high-definition (300 DPI) compared to older, compressed legacy files. Check that files are tagged with the correct Artist Name Original Release Date 4. Important Considerations Storage Requirements: A high-quality collection of 1,500 issues can exceed of storage space. For the best experience, use dedicated comic readers like CDisplayEx (Windows) or
(iOS) to handle the specific formatting of these digital files.
This collection contains explicit adult content. Ensure compliance with local laws and age requirements before accessing or distributing these materials.
The Fansadox collection by DoFantasy, reaching a 1500th issue milestone, represents a significant archive of adult digital comics that showcases the evolution of artistic styles from traditional to 3D modeling. This extensive collection is valued by collectors for tracking genre trends, maintaining artist portfolios, and documenting the progression of digital art over several decades. For more information, visit the official DoFantasy website.
Title: dofantasy Fansadox Collection — 1500 Complete (Brand New)
Description: Complete Fansadox "dofantasy" Collection — 1500 Volumes — Brand New
Notes:
If you want this rewritten in a different tone (short ad, auction listing, SEO-optimized listing, or marketplace format like eBay/Amazon), tell me which style and any specifics (price, location, payment methods).
DoFantasy Fansadox Collection 1500 Complete New
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The DoFantasy Fansadox Collection 1500 represents a massive digital archive from DoFantasy, a publisher known for its extensive library of adult-themed BDSM comics and illustrations. This "complete new" version typically refers to an updated compilation that includes high-resolution digital scans and reorganized file sets for better accessibility. Overview of the Collection
The Fansadox series is a long-running franchise featuring graphic adult content, primarily focused on themes of power exchange, bondage, and extreme fetishes.
Massive Volume: A full collection of 1,500 issues represents well over a decade of production.
Artistic Diversity: The collection features work from a variety of notable studio artists such as Badia, Tempter, Kali, DeCastro, and Alexi.
Format: Files are typically distributed in high-quality PDF, CBR, or CBZ formats to preserve the detailed artwork. Contents and Themes
Each issue in the collection generally ranges from 45 to 150 pages and is fully rendered in color.
Series Highlights: The collection includes various sub-series such as Voyages of the Trader, The Collector, and Women in Peril.
Adult Themes: Common themes found in the collection include slave auctions, kidnapping scenarios, forced labor, and various forms of BDSM play.
Digital Standards: Modern versions of this collection often feature "fixed" or "patched" files to ensure proper metadata tagging and compatibility with modern comic readers like CDisplayEx. Technical Considerations
Managing a collection of this size requires significant digital infrastructure:
Storage Requirements: A high-quality collection of 1,500 issues can exceed several dozen gigabytes of storage space.
Organization: Collectors often look for versions that are categorized by artist name and original release date for easier navigation.
Disclaimer: This collection contains explicit adult content intended for mature audiences. Accessing or distributing these materials must comply with local laws and age requirements. For official releases and previews, users can visit the DoFantasy Products Page. Dofantasy Fansadox Collection 1500 Complete New Patched
DoFantasy Fansadox Collection 1500 Complete New: A Comprehensive Review
The DoFantasy Fansadox Collection 1500 is a comprehensive and highly sought-after compilation of fantasy and adult art, featuring the works of various artists from the Fansadox stable. This review aims to provide an in-depth look at the collection, highlighting its key features, strengths, and weaknesses. dofantasy fansadox collection 1500 complete new
Overview
The DoFantasy Fansadox Collection 1500 Complete New is a digital collection comprising 1500 high-quality images, showcasing a diverse range of fantasy and adult art. The collection includes artwork from various artists, each with their unique style and flair. The compilation is designed to cater to fans of fantasy, sci-fi, and adult art, offering a vast array of visuals to explore.
Key Features
Strengths
Weaknesses
Conclusion
The DoFantasy Fansadox Collection 1500 Complete New is an outstanding compilation of fantasy and adult art, offering an unparalleled variety of high-quality images from multiple artists. While it may not be suitable for all audiences due to its mature content, it is an invaluable resource for fans of the genre. The collection's organization, ease of navigation, and exceptional image quality make it a must-have for enthusiasts.
Rating: 4.5/5
Recommendation
The DoFantasy Fansadox Collection 1500 Complete New is highly recommended for:
However, due to the mature content, it is not recommended for:
Final Verdict
The DoFantasy Fansadox Collection 1500 Complete New is a remarkable compilation that delivers on its promise of providing an extensive and diverse collection of fantasy and adult art. With its high-quality images, ease of navigation, and unparalleled variety, it is an essential resource for fans of the genre.
Fansadox Collection (often associated with ) is a long-running series of adult comic books and graphic novels that focus on various fetish and BDSM themes. A "1-500 Complete" collection refers to a massive digital archive containing the first 500 issues of this series. What is the Fansadox Collection
The collection is an anthology series featuring work from various international artists. Each issue typically focuses on a self-contained story or a specific theme. It is widely known in adult media for its high-quality artwork and niche fetish content. Guide to the "1-500 Complete" Collection
If you are looking for a guide to navigate or manage a collection of this size, here is a breakdown of what to expect and how to organize it: Content Variety
: The first 500 issues cover a vast range of themes, from classic BDSM and "damsel in distress" tropes to more extreme or specialized fetishes. Artist Diversity
: You will find distinct styles from well-known artists in the genre, such as G.W. Miller
. Each artist often has their own dedicated sub-series within the collection. File Format : These collections are usually distributed as (comic book archives) or Organization
: Because there are 500 individual files, they are typically organized by: Issue Number Fansadox 001 - Title
: Grouping by creator helps if you prefer a specific art style. Thematic Tags
: Many users use digital comic readers to tag issues by specific tropes. Recommended Tools for Viewing
To view a collection of this scale efficiently, you should use a dedicated digital comic reader rather than a standard image viewer: CDisplayEx
: A lightweight, popular choice for Windows that handles CBR/CBZ files smoothly. Chunky Comic Reader Notes:
: Excellent for iPad/iOS users who want to sync large collections from cloud storage or local servers.
: Good for power users who want to manage a library with detailed metadata and "smart folders." Important Considerations Content Warning
: This collection contains explicit adult material intended for audiences 18+ (or 21+ depending on your region). It covers "darker" fantasy themes that are not intended for general audiences.
: If you are acquiring this collection online, ensure you are using reputable sources and scan all files for malware, as large digital archives from unofficial sources can sometimes be used to hide malicious software.
This collection represents decades of creative work from a wide array of artists, including well-known names like Tempter, Kali, and DeCastro. Understanding the Fansadox Collection
The Fansadox series is a specialized category of adult art that focuses on dark fantasy, power dynamics, and BDSM themes. While individual albums are sold officially on the DoFantasy website, massive bundles like the "1500 Complete" set are typically unofficial, user-compiled archives found on third-party digital platforms. What is Included in the 1500 Set?
A complete 1,500-issue set is a significant digital asset that typically includes:
Diverse Artistic Styles: Early issues often feature classic comic art styles, while more recent releases (post-issue #1000) frequently use high-definition (300 DPI) digital painting.
Massive File Size: Because the collection spans over a thousand high-resolution PDF or CBR files, it requires substantial storage space.
Recurring Themes: The content primarily explores themes of bondage, discipline, and fictional power-exchange scenarios. Managing and Viewing the Collection
For collectors who acquire these massive digital libraries, specific software is recommended for the best viewing experience:
Desktop Readers: Tools like CDisplayEx are popular for Windows users to navigate the large comic files smoothly.
Organization: Newer versions of these "complete" sets often come "fixed" or "patched," meaning the files have been properly tagged with artist names and original release dates to help with sorting. Important Considerations
Legality and Piracy: Many "complete" collections circulating online are not official releases from the publisher and may involve digital piracy.
Content Warning: This collection contains explicit adult content, including graphic depictions of BDSM and non-consensual themes. It is intended for adult audiences only.
System Requirements: Due to the shear volume of data, ensure your device has sufficient memory and a capable PDF or comic reader to avoid performance issues. 15.168.143.205https://15.168.143.205 Dofantasy Fansadox Collection 1500 Complete New Patched
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The Fast5 files from a MinION run can become fairly sizeable, up to a few hundred gigabytes. Efficient and performant compression and indexing is therefore required.
For the most part the self describing and indexed nature of the HDF5 format ensures that data within a file can be quickly retrieved. However for a MinION run multiple Fast5 files are created each with a subset of the sequencing reads produced by the sequencer. Therefore finding the information pertaining to a read of a known ID cannot be done without a supplementary index cross-referencing the reads contained within in file; the alternative is to open all the files in turn and enquire about their contents. *The sequencing_summary.txt file produced by both MinKNOW and Guppy provides an index of the reads contained within in each Fast5 file*. This index can of course be reconstructed if required (as in the case of nanopolish index), though we recommend always storing the sequencing summary with the Fast5 data files.
Due to the large volume of data created by nanopore sequencing devices Oxford Nanopore Technologies has developed a bespoke compression scheme for ionic current trace data known as VBZ. VBZ is a combination of two open compression algorithms and is itself open and freely available from the Github release page. Ordinarily it will not be necessary to install the VBZ compression library and HDF5 plugin to simply use MinKNOW and Guppy as these software applications include their own copy of VBZ. However if you wish to read Fast5 files using third party applications (such as h5py) you will need to install the VBZ plugin.
The section above has given an outline to the data contained within a Fast5 file and how the file is arranged. Again for a more fulsome description of the contents of files users are directed to the ont_h5_validator project. In this section we will highlight several methods for manipulating the data contained within Fast5 files.
Oxford Nanopore Technologies provides a Python-based software for accessing data stored within a set of Fast5 files: ont_fast5_api. For the most part this set of tools hides from the user the need to understand anything about the nature of Fast5 files. Here we will show how to perform some common tasks that might be required when dealing with Fast5 files. For a guide in using ont_fast5_api programmatically please see the documention.
Since some older programs have not been updated to use multi-read files it can sometimes be necessary to convert such files to the deprecated single-read flavour. To do this run:
!rm -rf $output_folder/single-reads
!run multi_to_single_fast5 \
--input_path $input_folder --save_path $output_folder/single-reads \
--recursive
The output of the above command is a set of folders each containing a subset of the sequencing reads, one read per file. The filename of each read corresponds to the read's unique identifier.
!ls $output_folder/single-reads/0 2>/dev/null | head -n 5
00058fe1-e555-4a64-a41b-7f58fb7d6d6b.fast5 000dd482-c0d5-4520-aa86-8ee8bb61fd58.fast5 00158d74-4b7f-445a-b0ac-e1606f6c09b7.fast5 004a0bd2-edcf-4c2c-89bc-009a232cdb6a.fast5 0057b9d1-e566-4518-8b81-f69b30c6da99.fast5
A similar program exists to convert single-read files to multi-read files. We recommend that all datasets are updated to multi-read files for longer term storage. Here we will convert the single-reads created above back to multi-read files:
!rm -rf $output_folder/multi-reads
!run single_to_multi_fast5 \
--input_path $output_folder/single-reads --save_path $output_folder/multi-reads \
--filename_base prefix --batch_size 8000 --recursive
| 3 of 3|####################################################|100% Time: 0:00:55
The output of this command is a single directory containing all multi-read files. The filenames are prefixed with prefix as taken by the --filename_base argument of the program. The --batch_size argument here controls the number of reads per file:
!ls $output_folder/multi-reads
filename_mapping.txt prefix_0.fast5 prefix_1.fast5 prefix_2.fast5
The filename_mapping.txt cross-references the data from the input files with the output files.
!head $output_folder/multi-reads/filename_mapping.txt
26cb0f7d-8db2-4e2d-aa4e-9d273ccf1d66.fast5 analysis/multi-reads/prefix_0.fast5 b4441e24-a5d3-4357-bc24-4a169520d096.fast5 analysis/multi-reads/prefix_0.fast5 5d63b4ae-e9c7-43cb-b73c-7b3bc7facd57.fast5 analysis/multi-reads/prefix_0.fast5 5880c8b8-5c67-45cd-9082-2be09a7fc1d4.fast5 analysis/multi-reads/prefix_0.fast5 77d557c6-2154-4792-ad2d-49c9ca5f4bdd.fast5 analysis/multi-reads/prefix_0.fast5 afa10699-8648-4e7a-8bec-86118f202e8d.fast5 analysis/multi-reads/prefix_0.fast5 fb15566d-370c-478e-a190-d4221407e500.fast5 analysis/multi-reads/prefix_0.fast5 34465bd4-2335-4390-8675-daef5390ea79.fast5 analysis/multi-reads/prefix_0.fast5 67b3c07c-c4db-40e9-a18b-c10c8eeb70f5.fast5 analysis/multi-reads/prefix_0.fast5 133ac0a7-54d4-4681-8653-49b174fe6e7c.fast5 analysis/multi-reads/prefix_0.fast5
As mentioned in the discussion above it can be useful to have an index of which reads are contained within which multi-read files. Usually this indexing is provided by the sequencing_summary.txt file output by MinKNOW and Guppy. However if it is lost, here's a way to recover the information:
# build a script that will do the work
with open("build_read_index.sh", 'w') as fh:
fh.write(
'''
echo -e "filename\tread_id"
find $1 -name "*.fast5" \\
| parallel --tag h5ls -f -r \\
| grep "read_.\{8\}-.\{4\}-.\{4\}-.\{4\}-.\{12\} Group" \\
| sed "s# Group##" | sed "s#/read_##"
''')
# run the script
!bash build_read_index.sh $input_folder > read_index.txt
The read_index.txt output file contains the simple index we desire:
!head read_index.txt
filename read_id /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 00085dbe-217a-40f2-90c0-3bb15669f32c /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 00237911-92b3-49b4-9d13-2ea6a2ded996 /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 0025338c-3ea8-4168-b999-fe7f7fd597ee /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 00408494-e245-401e-8c9a-575ee491971b /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 00485ea4-a2fc-4b75-9969-9f1b1ab997da /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 004fbd46-3565-4505-8ade-bfa5bffa499b /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 0067fb48-9e65-415a-966a-fbf25c62e730 /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 0091aa27-0f2f-4e79-bb6e-6bfa1629326b /epi2melabs/fast5-tutorial/sample_fast5/workspace/FAK42335_2bf4f211a2e2d04662e50f27448cfd99dafbd7ee_400.fast5 00a52e30-a584-4ed8-97cf-074c601b0403
The program fast5_subset within ont_fast5_api can be used to create a new file set containing only a subset of reads.
The sample data contains data from a microbial mock community. Using the accompanying BAM alignment file lets find the reads with align to a single reference sequence:
!rm -rf read_list.txt
!echo "read_id" > read_list.txt
!samtools view fast5_sample.bam lfermentum \
| awk '{print $1}' \
| tee -a read_list.txt \
| echo "Found" $(wc -l) "reads"
Found 1100 reads
We can now use this file with the subsetting program:
!echo $input_folder
!rm -rf $output_folder/lfermentum
!run fast5_subset --input $input_folder --save_path $output_folder/lfermentum \
--read_id_list read_list.txt --batch_size 8000 --recursive
/epi2melabs/fast5_tutorial/sample_fast5 | 1105 of 1105|##############################################|100% Time: 0:00:02 INFO:Fast5Filter:1100 reads extracted
Analyses groups¶It can be the case that it is desirable to remove the Analyses groups from multi-read files. For example if live basecalling were performed during a run but these results are not wanted before data is archived.
To accomplish this task we will use the compress_fast5 program with the --sanitize option:
!rm -rf $output_folder/sanitized
!run compress_fast5 --input_path $input_folder --save_path $output_folder/sanitize \
--compression vbz --recursive --threads 8 --sanitize
| 5 of 5|####################################################|100% Time: 0:00:12
This achieves an approximate 3.5X reduction in filesize:
!du -sh $input_folder $output_folder/sanitize
2.4G /epi2melabs/fast5_tutorial/sample_fast5 682M analysis/sanitize
In this notebook we have introduced the Variant Call Format with an examplar file from the Medaka consensus and variant calling program. We have outlined the contents of such files and how they can be intepreted with a selection of common software packages.
The code tools presented here can be run on any dataset from an Oxford Nanopore Technologies' device. The code will run within the EPI2ME Labs notebook server environment.