Implementation of Hidden Markov Model (Viterbi) algorithm for the identification of sequence variants.
Milestone | Scheduled Beginn | Scheduled Completion | Finished |
---|---|---|---|
Project Plan | 13.11.2019 | 20.11.2019 | |
Data Management Plan | 13.11.2019 | 20.11.2019 | |
Data acquisition | 20.11.2019 | 24.11.2019 | |
Working algorithm | 25.11.2019 | 20.12.2019 | |
transition matrix | |||
update ref and sam | |||
emission matrix | |||
HMM viterbi | |||
Comparison with other tools | 21.12.2019 | 29.12.2019 | |
Report | 06.01.2020 | 11.01.2020 | |
Hand in | 12.01.2020 | ||
Presentation | 20.01.2020 |
General info
ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/
Data that we need:
ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/NA12878/CompleteGenomics_normal/BAM/
Reference Sequences:
ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/technical/reference/phase2_reference_assembly_sequence/hs37d5.fa.gz
Additional information: https://lh3.github.io/2017/11/13/which-human-reference-genome-to-use
viHMM in Matlab: https://github.com/tangmanhd/vi-HMM