Banana Slug Genomics

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======Team 1 report: assembly with Meraculous======
=====Basic features=====
Published by the US Department of energy. Meraculous was initially designed for haploid assembly, but currently supports diploid assembly as well. The advantages of this assembler include multi-threaded and parallelized computation, absence of error-correction for faster processing, paired-end short reads compatibility (e.g., Illumina), efficient and conservative traversal of subgraphs of the de Bruijn graph, selection of kmer set, production of a set of maximal linear sub-paths of the de Bruijn graph, alignment of reads to assembly  in order to identify useful read-pair information and closure of gaps. Meraculous has been used to assemble //Pichia stipitis// genome, producing 15.4 Mb genome, 75 bp paired reads with 425x coverage. As a result, 95% of the genome was covered and an N50 = 101 kb was obtained.

=====Meraculous algorithm=====

  * Counts occurrences of each kmer in the data set.
  * Removes kmers whose frequency are below the user threshold.
  * For each kmer, counts the number of high-quality single-base extensions
  * Classifies the 5' and 3' ends of each kmer
  * Stores the extensions of kmers with a classification in a hash
  * Removes non-reciprocal linkages between kmers
  * Selects kmers at random and extend outwards to produce contigs
  * Aligns all reads to contigs via BLAST
  * Assembles contigs into scaffolds using paired-end data
  * Searches unaligned reads as potential gap-closers using mate-pair data

=====Meraculous limitations=====
  * The assembler relies on data with high quality in order to avoid error correction
  * Initial release did not support polyploid genome assembly due to allowing for linear subgraphs of the de Bruijn graph only
  * Low memory footprint
=====User experience=====
  * Requires an array of other scripts in other languages
  * Most of high level scripts are written in perl
  * Tested the program in small dataset and obtained contigs
=====Installation=====
  * Main issue was get all dependencies together 
  * There was one non-standard perl mode needed
  * Some scripts contain error but they aren't hard to fix.
=====Running Meraculous=====
  * Execute run_meraculous.sh scripts along with the configuration file
  * Configuration file contains info on where where data is and what format it comes in
  * It creates a timestamped folder that includes directories containing results of each step and executables to modify the run
  * Then you can check the errors that made a run fail and resume the run
  * Logs are informative
=====Overall impression=====
  * Straightforward to figure out what went wrong just requiring a basic understanding of Perl
  * Handles all directory creation for you
  * Logs are very useful
=====Error correction=====
  * Meraculous requires error correction and adapter removal. Trimming is unnecessary.
  * High error rates stop the assembler. Need to be removed.
  * Kmer size chosen directly affects assembly quality
=====KamerGenie=====
Meraculous requires an optimal kmer size for runs. KmerGenie is a program used to give optimal assembly kmer size by generating abundance histograms for many abundance histograms for many values of k. Here is a link that helped me understand KmerGenie: http://kmergenie.bx.psu.edu/.
=====Musket=====
=====Previous analysis=====
=====Future directions=====
Banana Slug Genomics

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