dlaehnemann/create-quant-seq-testing-dataset: v1.0.0

<p>First version of the workflow that runs through and produces reasonably sized QuantSeq testing data that can be used in regular continuous integration testing.</p&gt

dlaehnemann/rna-seq-conservative-fold-change-without-replicates: v1.0.1

<ul> <li>filter out transcripts with gfold value 0</li> </ul&gt

snakemake-workflows/dna-seq-short-read-circle-map: dna-seq-short-read-circle-map v1.1.0

<h3>Features</h3> <ul> <li>allow for lowercase platform specification in samples.tsv (<a href="https://www.github.com/snakemake-workflows/dna-seq-short-read-circle-map/issues/4">#4</a>) (<a href="https://www.github.com/snakemake-workflows/dna-seq-short-read-circle-map/commit/dae21408f949fe7b999f29226d1eb0a1e388ed8c">dae2140</a>)</li> </ul&gt

varlociraptor/varlociraptor: v8.4.2

<h2><a href="https://github.com/varlociraptor/varlociraptor/compare/v8.4.1...v8.4.2">8.4.2</a> (2023-11-09)</h2> <h3>Bug Fixes</h3> <ul> <li>out of bounds error in estimation of third allele probability (<a href="https://github.com/varlociraptor/varlociraptor/issues/403">#403</a>) (<a href="https://github.com/varlociraptor/varlociraptor/commit/37eafa402865a9aa84d818233dc24dfeb301270a">37eafa4</a>)</li> </ul&gt

Drug interaction profiles are dynamic.

<p>(a) The degree of interaction, <i>I</i>(<i>T</i>) defined in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001540#s4" target="_blank">Materials and Methods</a>, is shown at different times from 12 h to 108 h: <i>I</i>(<i>T</i>) is negative for <i>T</i>≤24 h denoting synergy, but is positive for all <i>T</i>≥36 h denoting antagonism (vertical bars are s.e., 19 replicates). (b) A finer interaction measure than that used in (a), the degree of interaction obtained using the <i>α</i>-test defined in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001540#s4" target="_blank">Materials and Methods</a> produces a locus of drug interaction measures as a function of time. Consistent with (a), this measure changes sign, indicating a change of interaction near 30 h (note: −<i>α</i> is plotted). (c) The smile-frown transition resembles a phase transition when applying the <i>α</i>-test to <i>i</i>(<i>θ</i>,<i>T</i>) derived from MC4100 density data: the grey line shows the optimal drug combination that minimises <i>i</i>(<i>θ</i>,<i>T</i>), the red line shows the maximising combination. As the drug interaction profile ‘inverts’, the short-term optimal therapy shifts over a very short period to become the worst therapy beyond approximately 30 h. (The <i>y</i>-axis varies from <i>θ</i> = 0 (denoting an ERY-monotherapy) to <i>θ</i> = 1 (for a DOX-monotherapy), s.e. is shown as a pair of dashed lines.)</p

The drug interaction profile, <i>i</i>(<i>θ)</i>, as defined in Materials and Methods.

<p>The drug interaction profile is closely related to the two ‘checkerboard’ diagrams shown in (a) and (c). In a checkerboard, the concentration of both drugs is given on the <i>x</i> and <i>y</i> axes, bacterial growth inhibition (or population density or some other fitness measure) is then plotted on the <i>z</i> axis. The contour of all concentrations that reduce this measure by half is an <i>isobole</i> here denoted <i>IC</i>₅₀ and figures (a) and (c) show two checkerboard plots viewed from above. Basal concentrations of both drugs that achieve the same inhibitory effect in this illustration are <i>D</i>₅₀ and <i>E</i>₅₀, <i>θ</i> then parameterises the equidosage line between these two values. The fitness measure evaluated along this line is shown in (b) and (d) and we define the degree of interaction based on this curve, this is <i>i</i>(<i>θ</i>). We say the interaction is <i>synergistic</i> when the drug proportion that minimises <i>i</i>(<i>θ</i>) satisfies 0<<i>θ</i><1 as in (b), we denote the resulting value by <i>θ</i>_syn. In (d) we observe <i>θ</i>_syn = 0 or <i>θ</i>_syn = 1, in this case the drugs are said to be <i>antagonistic</i> as <i>i</i>(<i>θ</i>) is maximised by some drug combination and minimised by the monotherapies.</p

Smile-frown transition: a verbal argument and a toy mathematical model.

<p>(a) Synergistic drugs suppress drug-susceptible sub-populations (yellow cells) more than single-drug therapies however, this eliminates competitors of the drug-resistant red cells who grow more rapidly than the yellow cells would have done at weaker synergies. Thus greater synergy can increase population densities. (b) Solving <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001540#pbio.1001540.e001" target="_blank">Equation 1a</a>–<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001540#pbio.1001540.e002" target="_blank">b</a> and plotting population density against drug proportion shows that a short-term synergistic combination (blue) can maximise densities later (red). The red dots show the path of the optimal combination, note this idealised model is symmetric about <i>θ</i> = 1/2 but empirical data will not be. (c and d) The densities of drug-susceptible cells (<i>S</i> on the vertical axis in (c)) and resistants (<i>R</i> on the vertical axis in (d)) are shown at different times where, again, the blue line denotes a treatment of short duration and the red line denotes a longer treatment. The arrow in (c) represents the loss of <i>S</i> that occurs because of the drug whereas the arrow in (d) represents the analogous gain in <i>R</i>. For longer treatments the latter more than compensates for the former and by summing the red and blue lines in (b) and (c), respectively, we obtain the red and blue curves showing population density, Δ = <i>S</i>+<i>R</i>, in (a).</p

Drug checkerboards and isobolograms.

<p>(a) Empirical dose-response checkerboards show population density data on the <i>z</i>-axis versus drug concentration on the x and y-axes. This data was obtained by culturing <i>E. coli</i> sampled from the highly synergistic 50-50 environment at days one and five (the treatment with 4.8 µg/ml ERY and 0.08 µg/ml DOX), it corroborates the known synergism on day 1 and indicates the appearance of a more complex interaction by day 5. Note, 50% inhibition relative to the zero-drug control population is indicated by white blocks; (right) the 70% isobole is highlighted as a green line, indicating an interaction where one drug appears to suppress the other. (b) Isoboles (lines of equal inhibitory effect) are shown based on a numerical filter of the data from (a) (the fitting algorithm and code are described in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001540#pbio.1001540-DErrico1" target="_blank">[50]</a>). Black lines correspond to isoboles in intervals of 10% inhibition, the darkest red areas illustrate increasing drug concentrations with inhibition towards 100%, the darkest blue areas denote inhibition closest to 0%. The white region denotes 50% inhibition.</p

Overview of single nucleotide polymorphisms in the genomes of <i>E. coli</i> K12 (MC4100) that evolved within five days in erythromycin, doxycycline treatments or in a 50-50 combination of both.

<p>The number of polymorphic sites indicates how many independent nucleotide positions in the gene carry a SNP in at least one replicate, the frequency reflects the number of replicates where a polymorphism in the gene was found. The table only shows SNPs unique to the three treatments.</p