RNAseq-AB

Platform for performing and comparing differential expression RNA-seq results from EBseq & DEseq analysis with applicable add-ons of GFF3 data. Notably, this platform was used to assess transcriptomic data for Acinetobacter baumannii and is used as a reference for how the analysis was conducted as well as guidelines for a similar pipeline, not as a ready to use pipeline itself.

All Coding Files can be found in the "master" branch.

Expression files can be analyzed using two different statistical methods, DESeq & EBSeq. DESeq is more readily used by the scientific community but EBSeq is better known for experiments with low biological replicates.

Data required before use:

• Directory called exp3 with text files from RSEM expression analysis. Guided use of RSEM to produce appropriate results can be found in the Prep folder: "TerminalCodeRNASeq24PhrB.docx."
  • This directory should be housed with both .Rmd files.
• Directory called Genomes with the reference genomes (formed by GFF3 and Fasta files as described in "TerminalCodeRNASeq24PhrB.docx) and blast results as a text file (as produced by "TerminalCodeRNASeq24PhrB.docx)

EBSeq:

All differential expression analysis was done on RNASeqPhrB.Rmd file using R 4.1.2. To use this file, the directory exp3 & this document must be in the same directory.

Note: While DESeq using adjusted p-values to determine significance, EBSeq using False Discovery Rates (FDR) and PPDE (posterior probability for DE).

Initial Output:

• found in directory RNASeqPhrB_files (unless changed by user in Rmd script)
• GeneFC**.csv = Data (PPDE, FC, expression levels) for all genes. This is what would be used as the expression file uploaded to NCBI.
• FinalMatrixDE**.csv = Same as above but ONLY for differentially expressed genes

Analyzed Output:

• found in directory EBSeq
• Final<>EB.csv = FinalMatrixDE but with BLAST information included (Protein ID, alternative locus b/n A!S and ACX60 genomes) using the python script.
  • Note: You can color-code and sort with an excel file but be sure to save as a new excel file.
  • ALL indicates ALL genes rather than just DE genes
• Vennattempt = Venn diagram produced from R block Visualization

DESeq:

All differential expression analysis was done on RNASeqDEseq.Rmd file using R 4.1.2. To use this file, the directory exp3 & this document must be in the same directory.

The comprehensive report produced by DESeq can be produced as a html file by running the Visualization block of code (lines 142-146).

Output:

• found in directory exp3
• <>_norm.csv = normalized expression values for each gene
• <>_results = differential expression results with log2FC, p-values, and normalized expression values for each gene
• DESeq/DESeqBlsA.csv = _results but with BLAST info included (Protein ID, alternative locus b/n A1S and ACX60 genome) using the python script Comparing results Final.py.

Applicable versions/parameters:

• Trimming - Trim Galore vs 0.6.6 - Cutadapt vs 3.5 - Quality Phred score cut off of 20

• Reads that aligned using bowtie2 • R 4.1.2