rchikhi

# nthash1, pure python implementation
#
# (not nthash2, so only for k values < 64)
# ported from https://github.com/luizirber/nthash/

h = {'A': 0x3c8b_fbb3_95c6_0474,
     'C': 0x3193_c185_62a0_2b4c,
     'G': 0x2032_3ed0_8257_2324,
     'T': 0x2955_49f5_4be2_4456,
     'N': 0}

rchikhi

Wheeler graphs

Gagie, Manzini, Siren
Theoretical Computer Science, 2017
https://www.sciencedirect.com/science/article/pii/S0304397517305285

Notes of a whiteboard presentation to the Bonsai team in Lille.
These notes largely follow the paper.
Rayan Chikhi, 2019

rchikhi

This document is a partial presentation of the RopeBWT2 pre-print

http://arxiv.org/abs/1406.0426

It is the transcript of a presentation made within the Medvedev group at Penn State
in July 2014. It focuses on illustrating some notions from the methods, and 
illustrating and proving Algorithm 1. While this document does not cover the main 
contribution of the RopeBWT2 paper, I hope it can be helpful towards understanding 
the theoretical foundations that led to Algorithms 2 and 3.

rchikhi

#!/usr/bin/env python
doc = """
Quickly estimates insert sizes of read datasets, given some sequence(s) they can be mapped to.
Author: Rayan Chikhi         

short usage: <reference> <*.fastq> 

example: 
         estimate-insert-sizes contigs.fa readsA_1.fq readsA_2.fq readsB_1.fq readsB_2.fq