sauravdhr / ichor

Inference of the primary Case in Hepatitis c OutbReaks (ICHOR)

ICHOR

HCV directionality prediction software implemented in python
Based off Pavel Skums' QUENTIN https://github.com/skumsp/quentin
Call this program on a suspected cluster of clinical samples of viral dna for transmission network inference
Python 3.3 code

Prerequisites

python modules which are not in the standard library

numpy
scipy
fastcluster
six
biopython
networkx
cvxopt
pygraphviz

other prerequisites

lsqlin.pyc (included on this github) - https://github.com/scivision/airtools/blob/master/airtools/lsqlin.py graphviz, http://www.graphviz.org/
mafft, http://mafft.cbrc.jp/alignment/software/

Usage Information

This is primarily a command line utility program. To run, type something along the lines of

python ichor.py spreader.fas target.fas

this will run the program assuming lsqlin.py, ichor.py and the hcv fasta files are all in the current working directory. Your output (default tmp.png) should look similar to exampleout.png For help with other options, simply type

python ichor.py -h

If you have any questions, you can reach me at [email protected]

A note about input/output formatting

Input must be a valid FASTA file. This program expects viral quasispecies populations (a pool of closely related mutants achieved through deep amplicon sequencing) For each entry, your sequence ID should end with a number following the trailing underscore which denotes the frequency of that variant. For example, here we have a sequence ID with a bunch of extra information that will give the appropriate frequency of 25 for that variant

>P06_run12_alaska_3_2_25

Acknowledgements

Valeriy Vishnevskiy - lsqlin.py Pavel Skums - came up with the algorithm for QUENTIN, a precursor to ICHOR The rest of the DVH bioinformatics team @ CDC