Double-hung with curtains

• fixed issue with L and U being too close to each other. Smudgeplot simply creates a wild plot of the data that are fed to it regardless of being harder for interpretation (aligned with "honest data reporting" philosophy of smudgeplot, but might cause more confusion, perhpa we will add some more warnings in the future)

Double-Hung

Adding a new feature smudgeplot extract for extracting kmer pairs from a rectangle of the smudgeplot.

Great thanks to @zhenzhenyang-psu !

Documentation: https://github.com/KamilSJaron/smudgeplot/wiki/smudgeplot-extract
For usage see smudgeplot.py extract -h

Still Single Hung

This release is just to get it to Zenodo, otherwise identical to v0.2.2.

Single-Hung

This version updates:

• the annotation algorithm for higher ploidy levels based on simulations.
• encourages using of our KMC that speeds up the search for kmer pairs a lot
• adding a new warnings for mismatching estimates of 1n coverage by different approaches (was silent before)
• change in terminology, instead of "estimated ploidy" we say "proposed ploidy", as there is no model explicitly tested

Single-Hung

• fixed logging (now it's directed to err stream)
• an estimate of ploidy based on all smudges of that ploidy (instead of the ploidy of the brightest smudge)
• smudgeplot interface uses .py suffix to meet community standards

Single-Hung

This version is using the same computational backend as the previous version (0.1.3), but it's wrapped in a single interface that is expected to be kept in future:

smudgeplot <task> <arguments>

Further adjustments:

• improved algorithm for placing smudges on the plot for higher ploidy levels than 4
• alternative algorithm for extracting kmers available (--middle in hetkmers task)

I had no idea how to name the release, so I have decided to name individual versions of smudgeplots by types of windows, so let's start simple: Single-Hung it is. Hopefully, it will be good enough name to carry all the smudges.

beta3 - More modest algorithm for guessing 1n coveage, no default filtering

• no quantile filtering by default, a new parameter -q to set up the filter, the falg --no-qunatile-filtering was removed (set -q 0.99 to set up the previously default filter)
• algorithm for peak identification was failing if AAB was absent but AAAABB was present. This problem should be resolved by now by considering both the diploid and triploid 1n estimates.
• fixed the installation instructions
• minor fixes

beta2 release

• switch to colorblind friendly palette
• parameter nbins is autoscaling by default and fixed if defined by user
• added an option to disable quantile filtering (--no_quantile_filt flag)
• improved interface & README

beta release

smudgeplots are right now

• production ready (fingers crossed)
• scaling for any genome size and read set (tested on a dataset of 1,000,000,000 kmers)
• fully automated (tested on set of 25 obscure genomes)
• equipped with rich set of warnings whenever the inference seems strange

pre-beta release

This is the first draft of automated smudgeplots - plots that reveal genome structure without any assumptions about assembly, mapping and base quality scores.

Right now we have:

• non-optimized python script to extract kmer pairs
• Rpackage and R scirpt to generate a smudgeplot out of the extracted kmers
• a small R smiplet to guess L/U thresholds for kmer filtering

Everything should be operational, but it was not extensively tested