kir-reducer

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  Analysis of the tool

Inspiration

We wanted to tackle the challenge of analyzing KIR (Killer-cell Immunoglobulin-like Receptor) genes for leukemia treatment and their classification.

What it does

Right now, we have solved to first step of executing tools such as ("kir-mapper") to obtain the genotyping of patient data.

The objective of kir-reducer in future work is to analyse and recommend treatments for detected kir cells. This will be future work.

How we built it

We have spend most of the time configuring and executing existing tools. Then, we have run a set of python scripts on top to process results and obtain some first insights.

Challenges we ran into

The biggest challenge was dealing with technical issues, processing time and testing the different tools in order to undertand them. Also we have delved on possible ML architectures that we could use in a future analysis.

Accomplishments that we're proud of

We successfully run a couple of this tools, obtained initial results and were able to develop a first baseline ML model.

What we learned

We learned just how complex cell genetics are and the importance of precise bioinformatics pipelines.

What's next for kir-reducer

In the future, we would like to study possible analyses and integrate a holistic pipeline that is able to not only map (i.e., by using tools such as kirr-mapper), but also reduce (e.g., by our analysis).

Built With

• love
• python