BIOINFORMATICS

I need to use Galaxy to set up an experiment on some given files, but I am unsure how to begin.

1. I am distributing a Galaxy History called: CG19FinalProjectDNADatasets containing:
   • Sacce1_AssemblyScaffolds.fasta <- Saccharomyces cerevisiae Wild-Type Genome
   • Sacce1.ExternalModels.gff3 <- Saccharomyces cerevisiae Wild-Type Genome Annotations
   • Scerevisiae_RAMutant_Genome.v02.fa <- Saccharomyces cerevisiae Mutant Genome
   • Sacce1_chrVI-VII-VIII.fasta <- Saccharomyces cerevisiae Chromosomes VI/VII/VIII Wild-Type Genome
   • All Datasets are from the Wild-Type Genome
   • Dataset01:
     • SRR352492.sra_1.fastq
     • SRR352492.sra_2.fastq
   • Dataset02:
     • SRR352384.sra_1.fastq
     • SRR352384.sra_2.fastq
   • Dataset03:
     • SRR452441.csra_1.fastq
     • SRR452441.csra_2.fastq
   • The Datasets have already been Quality Controlled
   • Saccharomyces cerevisiae Wild-Type Chromosomes VI/VII/VIII is being provided for you to test/optimize your mapping conditions
2. Your task is:
   • To use these NGS Datasets to identify any polymorphisms that might be present in theSaccharomyces cerevisiae Mutant Genome
   • You are welcome to validate your findings using other methods (e.g., alignments, Blast, etc), but your primary conclusions must be based on NGS Reads mapping
   • Your findings must also be validated by IGV figures displaying the presence/absence of the polymorphisms you have identified. In other words, each polymorphism claim must be supported by an IGV figure
   • All your findings must be properly documented
   • A Final Project Report and Final Project Presentation must be prepared according to the instructions outlined below
3. Recommendations:
   • Start by looking at your data, study the data
   • Design a logical and simple Experimental Strategy. Remember there is no a single way to address this problem
   • Learn how to use and try to understand the following tools in Galaxy:
     • Bowtie map reads against reference genome (output = unsorted sam file)
     • Bowtie2 - map reads against reference genome (output = sorted bam file)
     • After you settle on Bowtie and/or Bowtie2, do not change this parameter
     • Pay special attention to the options provided to generate files containing aligned and/or unaligned reads. Remember, you might need to use those parameters to demonstrate your assumptions or test your hypothesis
     • sort a BAM file <= Sorting is imperative after the Bam file is generated and before other processing can occur
     • Flagstat tabulate descriptive stats for BAM dataset
     • BAM mapping statistics samtools idxstats
     • Filter BAM datasets on a variety of attributes
     • BAM-to-SAM convert BAM to SAM and SAM-to-BAM convert SAM to BAM (when needed)
   • I suggest using the test chromosome you must decide on which one of these tools is best for you task
   • Display the data on IGV
     • When using BAM files, remember to download, in addition to the BAM file, its accompanying BAM_INDEX file
   • If you need to assemble reads, let me know, and I will show you how to do it
   • Include Controls