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
In every fashion photoshoot, Lucia controls the narrative through her eyes. Whether she is shooting for a minimalist Scandinavian brand or a maximalist Italian label, her gaze shifts from vulnerable to confrontational within a single roll of film. Photographers like Mario Testino’s protégés have noted that her ability to micro-adjust her eye intensity is what elevates a standard commercial shoot to high art.
In an era where fashion imagery is often dominated by hyper-commercial gloss and digital perfection, the work of Slovak fashion photographer and stylist Lucia Javoreková offers a distinct and necessary counterpoint. Her portfolio—a carefully curated style gallery of photoshoots—transcends mere product documentation to become a study in mood, texture, and the fragile intersection between humanity and clothing. This paper examines the defining characteristics of Javoreková’s photographic style, her approach to the fashion photoshoot as a narrative medium, and the unique aesthetic language that makes her gallery a cohesive artistic statement.
Javoreková’s style gallery—the edited collection of her work—functions as a unified visual lexicon. Thematically, three recurring motifs define her gallery:
At the core of Lucia Javoreková’s work is what can be termed “ethereal minimalism.” Unlike the stark, high-contrast minimalism of 1990s Calvin Klein campaigns, Javoreková’s images breathe with a soft, diffused light. Her color palette leans heavily on desaturated earth tones, muted pastels, and the quiet gloom of overcast Central European skies. Whites are never purely white but take on hints of grey, cream, or blue.
This signature is not an accident of post-production but a deliberate choice during the photoshoot. Javoreková frequently shoots with natural light—often in liminal spaces such as decaying interiors, foggy forests, or sparse, modernist architecture. The resulting texture is almost painterly, reminiscent of the soft focus of 19th-century Pictorialist photography or the subdued domestic scenes of Vilhelm Hammershøi. This approach elevates the fashion subject from a commercial object to an artifact within a larger, melancholic landscape.
Why does the search for lucia javorcekova photos fashion photoshoot and style gallery continue to rise, while other models fade into obscurity? It is the ratio of versatility to recognizability.
Lucia Javoreková’s fashion photoshoots and her resulting style gallery represent a significant contribution to contemporary visual culture. By prioritizing atmosphere over advertising, narrative over novelty, and texture over trend, she has forged a signature that is immediately recognizable. Her work reminds us that fashion photography need not shout to be seen; it can whisper, provided the light, the space, and the gesture are in perfect, melancholic harmony. In a fast-paced digital economy, Javoreková’s gallery stands as a quiet archive of patience, proving that the most enduring images are those that capture not just how a garment looks, but how it feels to live inside it.
Lucia Javorčeková has transitioned from a professional cyclist to one of Slovakia's most recognizable fashion and fitness icons, known for her bold aesthetic and cinematic editorial style
. Her fashion philosophy, often summarized as "be bold, never regular," is reflected in her high-energy photoshoots that blend athletic precision with high-fashion glamour. Fashion Photoshoot Themes
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Lucia’s style has evolved from athletic wear into a sophisticated mix of high-end couture and elevated street style. Beach & Resort Wear
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highlights a shift toward empowering content, sharing beauty tips and "good vibes" alongside her fashion updates. Street Style
: She frequently blends polished, tailored pieces with a "tailored attitude," often seen in major fashion hubs like London and Slovakia.
Lucia Javorcekova , also known by her married name Lucia Lachkovic
, is a Slovak-born model, artist, and fitness influencer. Known for her large following of over 4.4 million on lucia javorcekova nude photos extra quality
, she has transitioned from a professional cycling and modeling career to focusing on digital creation and contemporary art. Career Evolution and Public Image Modeling and Cycling
: Lucia gained early international fame as a "sexy cyclist," which helped launch her high-profile modeling career. Fitness Influencer
: She is a prominent fitness figure, regularly sharing workout routines, such as glute-focused sessions involving squats and deadlifts, with her audience. Transition to Art
: In recent years, she has pivoted toward creative direction and contemporary painting, showcasing her work on dedicated art platforms and participating in residencies like the 2026 Arts Center Residency in New York. Content and Platforms
Lucia is active across several major social platforms, though she has recently withdrawn some identifiers from certain adult-oriented sites like OnlyFans. Lucia Lachkovic (@luciia) • Instagram photos and videos Lucia Lachkovic (@luciia) • Instagram photos and videos.
Lucia Javorčeková 's career has evolved from professional cycling into a global brand as a high-profile fashion model and content creator
. Her gallery showcases a blend of bold athletic roots with high-end editorial aesthetics, often featuring striking contrasts like leopard print paired with vibrant colors or sleek neutral silhouettes. Style & Photoshoot Highlights
Her photoshoots frequently emphasize structural elegance and bold confidence: Athletic Heritage
: Her fitness modeling often features high-performance gear like gray sports bras and leggings, maintaining a "be bold" aesthetic. Editorial Elegance
: Recently, she has leaned into timeless, composed looks for events like Milan Fashion Week, utilizing structural pieces like capes and tailored silhouettes to make powerful fashion statements. High-Contrast Aesthetics
: Her portfolio is known for diverse textures, ranging from leopard-print coats and bikinis to sleek black leather and monochrome suits. Artistic Vision
: Collaborations with photographers often explore colorful, life-driven themes using professional gear such as Leica SL cameras for high-detail captures. Emerging Career Trends for 2026
In 2026, Javorčeková's influence continues to align with broader industry shifts: Runway Presence
: The industry is seeing a rise in independent models and veteran creators returning to the runway for major shows, such as Giorgio Armani. Diverse Representation
: There is a growing focus on models who pursue their passions at any stage of life, breaking traditional age limits in modeling. Global Participation
: High-profile figures are increasingly involved in international fashion circuits, including upcoming events like the Milestone Global Fashion Tour in Paris specific outfit details from her recent fashion week appearances or see a breakdown of the photographers she commonly works with?
The Allure and Controversy of Lucia Javorcekova: Unpacking the Fascination with Nude Photos
In the digital age, the line between public and private lives has become increasingly blurred. The proliferation of social media and the internet has created an environment where information, images, and videos can spread rapidly, often without consent. One individual who has found herself at the center of this phenomenon is Lucia Javorcekova, a Slovak model whose nude photos have garnered significant attention online. The keyword "Lucia Javorcekova nude photos extra quality" reflects a broader fascination with celebrity and model nudity, which raises complex questions about privacy, objectification, and the commodification of the human body. In every fashion photoshoot , Lucia controls the
The Rise of Lucia Javorcekova
Lucia Javorcekova, a Slovakian model, gained prominence in the fashion industry due to her striking features and captivating presence on social media. Her career trajectory is emblematic of many models who leverage platforms like Instagram and Twitter to build a personal brand and attract the attention of brands and agencies. However, the digital visibility that has contributed to her success has also led to controversies, particularly surrounding the circulation of her nude photos.
The Fascination with Nude Photos
The interest in Lucia Javorcekova's nude photos, as indicated by the keyword "Lucia Javorcekova nude photos extra quality," is part of a larger cultural phenomenon where people seek out and consume images of celebrities and models in various states of undress. This fascination can be attributed to several factors:
The Impact on Individuals and Society
The spread of nude photos, whether consensual or not, has significant implications for individuals and society:
Navigating the Complexities
The case of Lucia Javorcekova and the search for "Lucia Javorcekova nude photos extra quality" serves as a microcosm for broader societal debates:
Conclusion
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Lucia Javorcekova is a stunning model known for her captivating presence on the runway and in front of the camera. Her fashion photoshoots are a testament to her versatility and impeccable style. Here are some highlights from her fashion photoshoot and style gallery:
Photoshoot Highlights:
Style Gallery:
Some popular fashion brands and designers she has worked with include:
Some popular photoshoots and campaigns featuring Lucia Javorcekova include:
Would you like to see more of Lucia Javorcekova's fashion photoshoots and style gallery?
Title: Unveiling Lucia Javorcekova's Svelte Style: A Glimpse into Her Fashion Photoshoot and Style Gallery
Introduction:
In the world of fashion, few names have been making waves as consistently as Lucia Javorcekova. This Slovakian beauty has been turning heads with her stunning looks and impeccable style, captivating audiences with her effortless elegance. Recently, Lucia Javorcekova's photos from a fashion photoshoot have been making the rounds, and it's clear that her style is more on point than ever. In this piece, we'll be taking a closer look at her fashion sense, highlighting some of her most striking images and exploring what makes her a standout in the fashion world.
Lucia Javorcekova's Rise to Fame:
Lucia Javorcekova's journey into the spotlight began when she started gracing the covers of top fashion magazines and walking the runways for prominent designers. Her unique blend of Slovakian charm and international appeal quickly made her a favorite among fashion enthusiasts. With her striking features, svelte physique, and captivating smile, it's no wonder she's become a sought-after model.
Fashion Photoshoot Highlights:
The recent fashion photoshoot featuring Lucia Javorcekova showcases her incredible versatility as a model. From edgy streetwear to high-end luxury, Lucia effortlessly transitions between styles, proving that she's more than just a pretty face. Here are some standout moments from the photoshoot:
Style Gallery Essentials:
When it comes to Lucia Javorcekova's personal style, there are a few key pieces that consistently make an appearance in her wardrobe:
What Makes Lucia Javorcekova's Style So Special?
So, what sets Lucia Javorcekova apart in the world of fashion? Here are a few factors that contribute to her unique style:
Conclusion:
Lucia Javorcekova's fashion photoshoot and style gallery are a testament to her status as a rising star in the fashion world. With her effortless elegance, versatility, and confidence, she's sure to continue turning heads and inspiring fashion enthusiasts around the globe. Whether you're a fan of high-end luxury or streetwear chic, Lucia Javorcekova's style has something for everyone – and we can't wait to see what she does next.
Lucia Javorcekova is a prominent Slovakian model recognized for a diverse portfolio blending high-fashion editorial, luxury swimwear, and fitness-focused aesthetics. Her gallery is characterized by Mediterranean influences, cinematic lighting, and versatility in both studio and outdoor location photography. Explore her professional portfolio to see her style evolution from professional cycling to modeling.
What sets Javorčeková apart from commercial fashion photographers is her resistance to the “catalog shot.” In her photoshoots, the garment is never the sole hero. Instead, she constructs scenes.
Consider one of her most circulated series: a shoot for a slow-fashion knitwear brand. Instead of posing the model against a seamless backdrop, Javorčeková placed her in a crowded tram at dusk. The model, wrapped in an oversized oatmeal sweater, is seen from a slight distance—her reflection in the window overlapping with passing neon signs. You see the sweater’s texture, yes, but you also feel the chill of the tram, the loneliness of the commute, the quiet dignity of the fabric against the city’s cold glass. That is Javorčeková’s genius: she sells a feeling that happens to wear clothes.
Her editorial shoots often feature:
To understand why lucia javorcekova photos consistently look like Vogue editorials (even when shot on an iPhone for a test), one must speak to the photographers behind the lens.
"Lucia requires almost no retouching," says fashion photographer Dmitri Volkov. "In our photoshoot for a swimwear campaign, the studio lighting hit her clavicle in a way that looked airbrushed straight out of the camera. Her style gallery doesn't need heavy filtering because she understands light placement better than some assistants I've hired."
Similarly, set designer Claire H. notes: "She interacts with props naturally. In a style gallery featuring antique mirrors, she didn't just stand there—she used the reflections to create double exposures herself. That is instinct, not direction." The Impact on Individuals and Society The spread
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.