BioNumPy

And we're now published in Nature Methods 🥳 Full article here: nature.com/articles/s4159…

Finally, a cool example showing that there are fewer mapped reads on average around genomic variants. Check out this colab if you want to try out the examples: colab.research.google.com/github/bionump…

.. or around transcription factor peak summits. Here we plot the pileup for reads on the positive and negative strand, and clearly see the pileups we expect around the summit.

BioNumPy has been updated with changes that make it a lot easier to work with genomic intervals and data on a reference genome 😀 Here are a few cool examples to illustrate the new stuff:

@vsbuffalo BioNumPy has some support for gtf files, but have not yet defined a complete set of abstractions for them. Would love suggestions for useful methods!

I'm curious now about how often we re-write bioinformatics code. You have to parse a GTF/GFF file in Python. What do you do?

@vsbuffalo BioNumPy tries to give a uniform interface for parsing common bioinformatics formats. Keeping the header information from input through analysis to output is under progress and will be in place for BioNumPy 0.3 github.com/bionumpy/bionu…

I think having unified comment metadata headers would go a long way. So often I lose column headers and metadata rows (i.e. starting with '#') when using the Unix data tools I love. We need a set of tools, even if simple wrappers, that preserve this important data.

So much of bioinformatics is endless writing of parsers for file formats written by software, and it just shouldn't be this way. This is needlessly time-intensive, bug-prone, and prevents higher-level abstractions from being developed. We need tidy bioinformatics.

Day 5/5 of short BioNumPy examples: Finding the most common kmers in a FASTQ-file. Try out the code here: colab.research.google.com/github/bionump… Check out our documentation for more cool examples: bionumpy.github.io/bionumpy🤠

Day 4 of small #BioNumPy examples: Sequence matching (searching for a sequence in a set of reads). Try out the code here: colab.research.google.com/github/bionump…

Day 3 of small BioNumPy examples: Plotting the mean base qualities across reads. Try out the code here: colab.research.google.com/github/bionump… .. and remember to follow us for daily examples😋

Day 2/5 of small BioNumPy examples: Motif matching. We download a motif from Jaspar, compute max motif score per read in a FASTQ file and plot a histogram of the scores. Run the code here: colab.research.google.com/github/bionump…

Every day this week, we'll share a small example of how BioNumPy can be used. First out: FASTQ filtering (try out the code yourself here: colab.research.google.com/github/bionump…) .. and remember to follow us for daily updates ☺️