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Case Study: Real-time Diagnostics from Nanopore DNA Sequencers

Posted on by Pavel Tantsiura
In this issue:

Data Analysis in Healthcare is a matter of life and death, and it’s also a very time-consuming task when you do not have the proper tools. When we are talking about sepsis – the dangerous condition when the body starts to attack its organs and tissues in attempts to fight off the bacteria or other causes – the risk of losing the patient due to sepsis increases by 4% with each hour.

The researchers from the University of Queensland and the Google Cloud Platform developers have teamed up with the APP Solutions developers to provide medical doctors with a tool to help patients before they suffer from septic shock.

With the emergence of nanopore DNA sequencers, this task becomes manageable and much more efficient. These sequencers stream raw data and generate results within 24 hours, which is a significant advantage, especially when doctors need to identify pathogenic species and antibiotic resistance profile.

The primary challenge, from the technical point of view, lies with data processing, which requires significant resources for processing and subsequent storage of incoming data. The APP Solutions team tackled the development of a cloud-based solution to solve this challenge.

About the Project: Nanopore DNA Sequencers

Our team worked on the cloud-based solution for the Nanopore DNA Sequencing, and we have developed a Cloud Dataflow integrated with the following technologies:

  • FastQ Record Aligner
  • JAPSA Summarizer
  • Cloud Datastore and App Engine
  • App Dashboard

The pipeline itself consists of the following elements:

  • Chiron base caller implemented as a deep neural-network
  • Detectors for species and antibiotic resistance genes
  • Databases for long-term experimental data storage and post-hoc analysis
  • A browser-based dynamic dashboard to visualize analysis results as they are generated

Overall, the system is designed to perform the following actions:

  • Resistance Gene Detection: this pipeline identifies antibiotic resistance genes present in a sample and points out actionable insights, e.g., what treatment regimen to apply to a particular patient.
  • Species Proportion Estimation: this pipeline estimates the proportion of pathogenic species present in a sample. Proportion estimation can be useful in a variety of applications including clinical diagnostics, biosecurity, and logistics/supply-chain auditing.

The software is open-source, built on the open-source packages:

  • JAPSA
  • TensorFlow
  • Apache Beam
  • D3

We have used Google Cloud to implement the data analysis application due to its scaling capacity, reliability, and cost-effectiveness. It includes a wide array of scalable features for Tensor Processing Units and AI accelerator microchips.

The transformation of information follows this sequence:

  1. Integration – files are uploaded to the Google Cloud Platform and streamed into the processing pipeline;
  2. Base-calling stage – machine learning model infers DNA sequences from electrical signals;
  3. Alignment stage – via a DNA database, the samples are analyzed to find pathogen sequences and other anomalies;
  4. Summarization stage – calculation of each pathogen’s percentage in the particular sample;
  5. Storage and visualization – the results are saved to Google Firestore DB and subsequently visualized in real-time with D3.js.

Watch the video about the project: 

Nanostream Project Tasks & Challenges

Ensuring Data Scalability

Nanopore Sequencer DNA Analysis is a resource-demanding procedure that requires speed and efficiency to be genuinely useful in serving its cause.

Due to the high volume of data and tight time constraints, the system needs to scale accordingly, which was achieved via the Google Cloud Platform and its autoscaling features. GCP secures smooth and reliable scalability for data processing operations.

To keep the data processing workflow uninterrupted no matter the workload, we used Apache Beam.

Refining Data Processing and Analysis Algorithms

Accuracy is the central requirement for the data processing operation in genomics, especially in the context of DNA Analysis and pathogen detection.

The project required a fine-tuned, tight-knit data processing operation with an emphasis on providing a broad scope of results in minimal time.

Our task was to connect the analytics application to the cloud platform and guarantee an effective information turnaround. The system was thoroughly tested to ensure the accuracy of results and efficiency of the processing.

Integrating with DNA Analysis Tools

DNA Analysis tools for Nanopore sequencers were not initially developed for cloud platforms and distributed services. The majority of the analysis tools were just desktop utilities, but this significantly limited capability. We needed to integrate the desktop-based DNA analysis tools into a unified, scalable system.

We have reinterpreted desktop-based DNA analysis tools for HTTP format and distributed them as web services, which made them capable of processing large quantities of data in a shorter timespan.

Securing Cost-Effectiveness & Reducing Overhead

Nanopore DNA Sequencers are a viable solution for swift pathogen analysis and more competent medical treatment. However, the maintenance of such devices can be a challenging task for medical facilities due to resource and personnel requirements. Also, the scope of its use is relatively limited in comparison with the required expenditures.

We moved the entire system to Google Cloud Platform to solve this issue, allowing the service to be accessed and scaled without unnecessary overhead expenses.

Developing Accessible User Interface

Machine learning and big data analysis systems can process much data, but it’s useless until the insights are presented in such a way that is understandable. In the case of the Nanopore DNA Sequencing solution, the idea was to give a tool to the medical staff that would help them make decisions in critical situations and save lives. Therefore, an accessible presentation was one of the essential elements of this research project.

The system needed an easy-to-follow and straightforward interface that provided all the required data in a digestible form, avoiding confusion.

To create the most convenient user interface design scheme, we have applied extensive user testing. The resulting user interface is an interactive dashboard with multiple types of visualization and reporting at hand that requires minimal effort to get accustomed to and start using it.

When it came to visualization, the initial format of choice was a pie chart. However, it was proven insufficient in more complex scenarios.

Because of that, we have concluded that there was a need to expand the visualization library and add a couple of new options, which was where the D3 data visualization library helped us out.

Throughout extensive testing, we have figured out that Sunburst diagrams are doing an excellent job of showing the elements of the sample in an accessible form.

Project’s Tech Stack & Team

There were many technologies involved, the majority of which had to do with big data analysis and cloud: 

  • JAPSA
  • TensorFlow
  • Chiron Base Caller
  • Google Cloud
  • Google Cloud Storage
  • Google Cloud PubSub
  • Google FireStore
  • Google Cloud Dataflow
  • Apache Beam
  • D3 Data Visualization Library
  • JavaScript

Related articles:

How to Pick Best Tech Stack for Your Project

Calmerry Telemedicine Platform Case Study 

From the APP Solutions’ side, we had four people working on this Nanopore DNA Sequencers project: 

  • 2 Data Engineers
  • 1 DevOps Engineer
  • 1 Web Developer

Creating Nanopore DNA Sequencing Cloud-Based Solutions

This project was an incredible experience for our team. We had a chance to dive deep into the healthcare industry as well as machine learning, data analysis, and Google Cloud platform capabilities.

While we were exploring the possibilities of data analysis in healthcare applications – we found out many parallels between data analysis in other fields.

We have managed to apply our knowledge of cloud infrastructure and build a system that is capable of processing large quantities of data in a relatively short time – and help doctors save patients’ lives!

Learn more about the project and check out our contributions to GitHub:

What our clients say 

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Google Play Store Optimization

Posted on by Pavel Tantsiura
In this issue:

Let me just outline, that currently there are over 2 million apps in Google Play Store. That is quite a good deal of applications, isn’t it?

Sounds like a piece of great news for all smart gadget users out there, but not as good for app developers.

Getting to ASO itself, which is basically app optimization for improving its’ ranking in App Store search results, the surprising thing is going on. A large amount of publishers still doesn’t invest in app store optimization.

But here is one thing – before people use apps for diverse purposes, they tend to search for these. Consequently, everybody wants the highest rankings in Android App Store, because you get more app downloads. It can sound simple in theory, but in fact, takes a while trialing and fixing mistakes.

While nobody really knows the exact algorithm of Google ranking, there are a few well-tried tricks that work to lift your app up in Play Store. Google Play Store algorithm seems to be more complicated when comparing to Apple App Store.

Here is a list of primary Google play store app ranking factors:

  • Number of ratings
  • Number of installs and uninstalls
  • App involvement (frequency of use)
  • Growth of downloads in the nearest 30 days
  • Backlinks to your app

In fact, there are a lot of common things in app optimization for Android and iOS. But let’s dive more into specific features of ASO Google Play Store, shell we?

7 game-changing tricks for Android app optimization

Google play optimization tricks

1. Find and track the keywords

This basic, yet deciding, step means EVERYTHING on your way to Google app store search optimization. Without this information, you won’t even find out whether your google play search optimization is working or not.

Apparently, it’s important to choose the words according to your target audience.

The keywords in Google Play Store you select should properly describe your app, so people are encouraged to download it once they find the app in the search. Besides, you want keywords to be as relevant to your application core as possible.

And to hit a maximum of your target audience, these words better be the most requested, at the same time overlapping competition as little as possible.

There are cases in-app publishing when particular apps gained about 300% downloads raise only from keywords optimization.

Remember not to overplay with this part to really improve Google Play ranking.

Tools for keywords research:

  • Google Keyword Planner
  • Wordstream
  • Sensor Tower
  • Wordpot
  • AppCodes
  • Ninja Search Combination Tool

You can also dig for more keywords either in users’ reviews (check Review Mining), or survey your target audience on Social Media, through e-mail newsletters, etc.

2. Include keywords in the title

Speaking about the name of your application, it might be the most determining factor in ASO.

First and foremost – keywords placed in the title of your application should be with the most massive search traffic. Take time to search for this essential, because once you decided on the title, it becomes a staple. And you really want the head of the app to be descriptive, unique, sharp, and appealing.

This way you create the most comfortable and “easy to figure out” experience for the searchers.

Once your app is published, starts getting downloads and reviews, it will be also spread by word of mouth. So it’s not the best idea of switching and trying different names at that stage.

Mind! Your title should not exceed 25-30 characters. Otherwise, you risk losing users distracted by not seeing a complete name in a search list and shifting to a bunch of other apps out there.

3. Description really matters…for Google

Here goes a major difference between Google Play Store and Apple App Store search optimization principles.

Google picks up the keywords from a description of your application. Obviously, we need to get the most out of it.

Experience shows that using keywords 4 to 5 times throughout the app’s definition will improve your rankings up to 20 spots. But again, do not stuff your description with the whole range of keywords straight – that’s a way to turning it into spam.

4. Now visuals – App’s Icon, Screenshots, Promo Video

Looking for an appropriate application, a lot of searchers will “window shop”. And the app’s icon is the first thing to pay attention to. It should be of high quality, utterly informative, and attractive design. There are also clear specifications Google expects your icon to include, so you can, obviously, Google it 🙂

Killer name and icon might be not enough for catching your prospect’s full attention. So make sure to use all 8 available screenshots for different types of devices – phones, tablets, TVs. You need a set of high-resolution screenshots with the descriptions on them to show the most goodies of your app.

To make these pics even edgier, use various dynamic tools (Promotee, Adobe Photoshop, PlaceIt, Screenshot Maker Pro) to simulate running the app on the device.

A stunning Promo Video is a cherry on the top of your cake. That is why Google Play is so awesome. You simply upload it to YouTube in a matter of minutes.

Make your video short and on point to respect your people’s time, they will appreciate that a lot! You wanna highlight only major features and advantages within your app.

5. Work those reviews and ratings up

App optimization in Google play store

The truth is it takes a number of downloads to get displayed. So asking for reviews and improving ratings of the app is a significant scope when doing a qualified ASO.

Zendesk claims in its’ recent survey that around 88% of consumers are mostly influenced by online product reviews before they make a decision to buy an app.

So again, head to your customers and ask to leave favorable reviews. As far as your app is satisfying and involving, it won’t be a problem for them.

For Google Play Store there is also a great chance to avoid negative reviews from users.

You can simply provide them with a clear direct channel for giving feedback to developers within the app. This way you can ask users for reviews (Important! Only when they are the most engaged, not really when they are busy performing tasks on the app, ok?). Just preface by asking a simple question – are you enjoying the app?

6. Localize your app

You always want to translate the application to the languages of your target regions. It’s a true must to offer a localized version of your product, except a common international option.

7. Backlinks are going to make wonders for your app

It’s the same as with a normal web search when links from reputable A list resources increase spreading the application over the net. You don’t wanna deal with low-quality Z list link farms for getting optimal results.

Therefore, it will be great to promote your app on some popular websites, asking them to write about your application and providing a link to your app page. You may also consider starting your own blog and contact press for people to get more opportunities for exploring your app.

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Overall picture

A global trend is all about the growing price of each app installation and the same rising number of downloads required to appear in the featured ratings of Google Play Store. So promoting the app can become a truly challenging activity for the narrowed budget companies.

At the same time, Google Play Store optimization can complete your whole marketing strategy at a lower cost and give tangible results already in the short-run. Don’t waste that chance and absolutely try it.

Happy app store optimization, guys!