File name Description Tcas5.2.fna.gz Tribolium castaneum reference genome (build 5.2) in fasta format. (X-chromosome and Autosomes only)
Tcas5.2.gff.gz Corresponding GFF file for the Tcas5.2 reference genome provided.
Control_R1.fastq.gz 3 Control replicates: R1, R2, R3 50bp single-end non-strand-specific reads
Control_R2.fastq.gz
Control_R3.fastq.gz
Primed_R1.fastq.gz 3 Primed replicates: R1, R2, R3 50bp single-end non-strand-specific reads
Primed_R2.fastq.gz
Primed_R3.fastq.gz
I have the following files and I need to return a. Provide a table listing all the genes that are significantly differentially expressed at adjusted p-value < 1e-10 and more than 4-fold up or down regulated (i.e. to be in the table it must meet both criteria)? The table should include columns for: 1) a unique gene identifier that can be looked up in NCBI databases (e.g. XM_001808014.3), 2) adjusted p-value, and 3) log2FC
b. Present a figure illustrating the differential expression between individuals and/or treatments. This could be as simple as the PCA plot from default DESeq2 output, but the possibilities are not limited to that. For example, you might learn how to do a volcano plot and include that.
c. For primed replicate #1 (Primed_R1.fastq.gz) how many SNVs show allele-specific expression bias? (define bias as SNV allele frequency > 0.7)
I know I have to use the RNA seq and The htseq .. Convert the GFF file to GTF file to do the htseq and then use the DESeq.
I want to know in what order should i do it and DO i need to use blast anywhere and what shoukd be the methods to solve this problem.
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There is no need to SHOUT. I have adapted your title to remove the uppercase characters. In addition, it would be better to split up your long thread in multiple, single-problem questions.
Sorry for the long post and I am definitely not shouting, My bad if it felt that way.
Can you help me with letting me know as to how should I approach this problem? I know that I have to do a RNA STAR on galaxy to get the bam file but should I do it on individual file or make a collection dataset of the control and a dataset for the prime ?
This looks like a homework or a bioinformatics test. Anyway, you can use EdgeR from Bioconductor for all. http://bioconductor.org/packages/release/bioc/html/edgeR.html
I want to use galaxy and I want to know if I need to trim any of my files ornot? Also . since each file of control and primed has three replicates do I need to form a collection dataset or run RNA STAR separately on each.
I have never worked with edgeR before so I am not sure If I will be able to do it by that.
You can check if you need to trim after you evaluate your raw data with FastQC, if you see adapters or low-quality regions, you definitively need to trim. After that, you can align your reads separately with STAR, each library could have some issues, so it's better to do it independently.