Results

General parameters¶

damage: The estimated damage in the specific taxa, \(D\). float64.
significance: The number of sigmas that the damage is away from 0, i.e. how certain one should be about there being non-zero damage. float64.
q: The damage decay rate. float64.
A: The background independent damage. float64.
c: The background. float64.
phi: The concentration for a beta binomial distribution (parametrised by \(\mu\) and \(\phi\)). float64.
rho_Ac: The correlation between \(A\) and \(c\), \(\rho_{Ac}\). High values of this are often a sign of a bad fit. float64.
XXX_std: the uncertainty (standard deviation) of the variable XXX for \(D\), \(A\), \(q\), \(c\), and \(\phi\).
MAP_valid: Whether or not the MAP fit is valid (defined by iminuit). bool.

mean_L: The mean read length of all the individual, unique reads that map to the specific taxa. float64.
std_L: The standard deviation of the above. float64.
mean_GC: The mean GC content of all the individual, unique reads that map to the specific taxa. float64.
std_GC: The standard deviation of the above. float64.
tax_path: The taxanomic path from the LCA to the root through the phylogenetic tree. string.

N_x=1_forward: The total number of “trials”, \(N\), at the first position in the forward direction, \(N(x=1)\). int64.
N_x=1_reverse: Same as above, but for the reverse direction, \(N(x=-1)\). int64.
N_sum_forward: The sum of \(N\) over all positions in the forward direction, \(\sum_i N(x=i)\). int64.
N_sum_reverse: Same as above, but for the reverse direction, \(\sum_{-i} N(x=i)\). int64.
N_sum_total: The total sum N_sum_forward and N_sum_reverse. int64.
N_min: The minimum of \(N\) for all positions (forward and reverse). int64.
k_sum_forward: The total number of “successes”, \(k\), summed over all positions in the forward direction, \(\sum_i k(x=i)\). int64.
k_sum_reverse: Same as above, but for the reverse direction, \(\sum_{-i} k(x=i)\). int64..
k_sum_total: The total sum k_sum_forward and k_sum_reverse. int64.
k+i: The number of “successes”, \(k\) at position \(x=i\): \(k(x=i)\) in the forward direction. int64.
k-i: Same as above, but for the reverse direction. int64.
N+i: The number of “trials”, \(N\) at position \(x=i\): \(N(x=i)\) in the forward direction. int64.
N-i: Same as above, but for the reverse direction. int64.
f+i: The damage frequency, \(f\), given \(k\) and \(N\): \(f(x) = k(x) / N(x)\), at position \(x=i\) in the forward direction. int64.
f-i: Same as above, but for the reverse direction. int64.