An online tool for assessing the mutational spectrum of epPCR libraries with poor sampling.
Error prone PCR is a method to create a pool of amplicons with some random
errors. For the best results the number of mutations and the spectrum of
the mutations needs to be controlled, hence the need for a test library.
The calculations of a test libray are slightly laborious and are affected
by the very small sample size. This calculator tries to overcome these
two issues by computing the mutational biases given a starting sequence
and list of mutant genotypes, by calculating the mutations per sequence
by fitting it to a Poisson distribution and by estimating the errors in
the values. In particular, the errors are calculated using the assumption
that a mutation and its complementary are equally likely in light of the
double helix nature of DNA (e.g. A to G on one strand will result
in T to C on the other). For the specific formulae used see this note about propagating
The program can calculate mutation frequencies from the list of mutations found and the template sequence or it can also accept the frequencies directly. The 'Demo' values are from an actual experiment.
There are two possible starting points for mutanalysts.
One is proving a sequence and the mutations sampled, for which the mutational load, mutational spectrum and the mutational bias indicators will be calculated.
The other is more downstream, wherein one proves a mutational spectrum and mutational load and the mutational bias indicators will be calculated.
In frame sequence that was mutagenised. Note that all symbols that aren't uppecase ATUGC, will be discarded along with a Fasta header (e.g. '>T. maritima Cystathionine β-lyase'), therefore for masked sequences use lowercase.
For Pedel-AA calculations, the library size is required.
This is the list of the mutations found. Identifying the mutations can
be done using the Mutantcaller tool.
The format is as follows:
The simplest estimate of the frequency of mutations per sequence is the average of the point mutations per sequence (m), however due to the small sample size this may be off. The distribution of number of mutations per sequence follows a PCR distribution, which can approximated with a Poisson distribution (Sun, 1995). In the latter, the mean and the variance are the same (λ —unrelated to PCR efficiency—). The sample average and variance may differ, especially at low sampling. The number to trust the most is the λPoisson.
The average is N/A mutations per sequence (N/A kb).
The sample variance is N/A mutations per sequence.
The λPoisson is N/A mutations per sequence.
If the λPoisson and average are very different and the plot is very poor, sequencing more variants from the test library may be reccomendable.
Rows represent the wildtype base, while columns the base in the mutant.
|Colour codes||Identity||Purine transition||Pyrimine transition||Transversion|
|Data display options||Raw data||Frequency normalised||Strand complimentary normalised|
Sequence-composition–corrected incidence of mutations (%):
|A→N, T→N (%)|
|Transitions (%) total|
|A→G, T→C (%)|
|G→A, C→T (%)|
|transversions (%) Total|
|A→T, T→A (%)|
|A→C, T→G (%)|
|G→C, C→G (%)|
|G→T, C→A (%)|
For details about pedel-AA see pedel-AA homepage.