| ```markdown | |
| # Goal/Experiment: | |
| The goal of this experiment is to provide an overview of the Genomics Research Center (GRC) data delivery structure and results files for bulk RNA sequencing (RNASeq) analysis. | |
| # Bulk RNASeq Delivery V.4 | |
| **Tyler Stahl** | |
| *Genomics Research Center* | |
| *Version 4 - October 17, 2023* | |
| ## Abstract | |
| This protocol will give an overview of the GRC data delivery structure and results files. | |
| ## Protocol Citation | |
| Tyler Stahl 2023. Bulk RNASeq Delivery. protocols.io https://dx.doi.org/10.17504/protocols.io.rm7vzzx9rgx1/v4 | |
| ## License | |
| This is an open-access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
| ## Protocol Status | |
| Working - We use this protocol and it's working. | |
| ## Created | |
| October 17, 2023 | |
| ## Analysis Overview | |
| The RNASeq analysis follows these stages: | |
| 1. Pre-processing (quality control/filtering/trimming) | |
| 2. Alignment | |
| 3. Post-processing | |
| 4. Feature quantification | |
| 5. Differential expression analysis between sample groups using DESeq2. | |
| A detailed overview of the analysis can be found in the `README.txt` and `RNASeq_methods.txt` files. Below is the workflow diagram for data processing. | |
|  | |
| ## Delivery Structure | |
| The delivery email includes three download links corresponding to: | |
| 1. Raw (fastq) files | |
| 2. Aligned (bam/bigWig) files | |
| 3. Results files | |
| ### Download Links | |
| - **RNA-Seq Analysis Results and QC:** [Download Link](https://grcweb.circ.rochester.edu/pickup/230821130441-10817/deliv_NHD13_GEO_results.tar.gz) (Checksum: 1e2e1da41926b5d45ef24c103c7a5f48e) | |
| - **RNA-Seq Analysis Aligned Data:** [Download Link](https://grcweb.circ.rochester.edu/pickup/230821130431-10715/deliv_NHD13_GEO_align.tar.gz) (Checksum: 3c57a3de7218cae0ded7f842b9b2fdd7) | |
| - **RNA-Seq Raw Data (for GEO submission):** [Download Link](https://grcweb.circ.rochester.edu/pickup/230821130423-10606/deliv_NHD13_GEO_raw.tar.gz) (Checksum: 59b130b3986ebc9174a75ef809db1ce2) | |
| **Note:** These URLs will expire in 10 days. | |
| To uncompress the delivery directory, use FREE compression software [7zip](http://www.7-zip.org). | |
| If you are on a PC, download compression software to unzip the folders. Macs have built-in zip software. | |
| ### FASTQ, BAM, and Results Files | |
| - **.fastq files:** Contain nucleotide and quality information generated from the Illumina Sequencer. | |
| - **.bam files:** Store alignment data and mapping quality scores in a binary format. | |
| - **Results folder:** Contains quality control information and results files from DESeq2. | |
| ## MultiQC Report | |
| MultiQC aggregates QC information from multiple different analysis outputs into a single interactive report. | |
|  | |
| ### General Statistics | |
| The general statistics include: | |
| - **Fastp:** % Duplication, GC content, % PF, % Adapter | |
| - **Star:** % aligned, M aligned | |
| - **Feature counts:** % assigned, M assigned | |
| - **Salmon:** % aligned, M aligned | |
| Each section is detailed below: | |
| #### Fastp | |
| - **Filtering statistics:** Metrics including read quality, read length, N-Content. | |
| - **Sequencing Quality:** Phred quality scores assigned to each base. A higher Phred score means higher confidence and lower error rate. | |
| - **N Content:** Percentage of ambiguous or unknown bases. | |
| - **GC content:** Proportion of guanine (G) or cytosine (C) bases in the RNA sequence. | |
| #### STAR Alignment | |
| - **Uniquely mapped:** Reads aligned to a single loci. | |
| - **Mapped to multiple loci:** Reads aligned to multiple loci. | |
| - **Mapped to too many loci:** Reads aligned to excessive locations. | |
| - **Mapped too short:** Reads aligned to genome but fall short of the filtering metrics. | |
| - **Unmapped: other:** Non-alignable reads. | |
| #### Feature Counts | |
| - **Assigned:** Reads assigned to a genomic feature (i.e., gene). | |
| - **Unassigned: Multi Mapping:** Reads aligning to multiple genomic features. | |
| - **Unassigned: No Features:** Reads that could not be aligned to any defined genomic features. | |
| - **Unassigned: Ambiguity:** Reads aligning to multiple features, categorized as `Ambiguity`. | |
| #### Salmon | |
| - **Fragment length distribution:** Refers to the distribution of fragment lengths generated in the sample. | |
| ## DESeq2 Results | |
| Two reports in the `deSeq2` folder: | |
| 1. Star-feature (gene-level) | |
| 2. Salmon (transcript level) | |
| ### Files in Star and Salmon Folders | |
| - **deSeq2_counts.txt:** Raw count values. | |
| - **deSeq2_NormCounts.txt:** Count values normalized with DESeq2's median of ratio. | |
| - **deSeq2_rlog_NormCounts.txt:** Log of the normalized counts. | |
| ### Comparison Files | |
| Example file: `deSeq2_NHD13_vs_WT.txt` | |
| | A | B | C | D | E | F | | |
| |--------|---------------|--------|---------|-----------|---------| | |
| | BaseMean | log2FoldChange | stat | pvalue | padj | | |
| | Hoxa9 | 636.168 | 2.557 | 21.331 | 5.92E-101 | 8.68E-97 | | |
| | Pbx3 | 456.879 | 3.091 | 20.932 | 2.76E-97 | 2.03E-93 | | |
| | Pbx1 | 401.557 | -3.27 | -16.477 | 5.38E-61 | 2.63E-57 | | |
| **Terms Definitions:** | |
| - **BaseMean:** Average expression level across samples. | |
| - **log2FoldChange:** Log2 fold change in gene's expression between conditions/groups. | |
| - **stat:** Test statistic to assess significance of differential expression. | |
| - **p-value:** Calculated using a negative binomial distribution. | |
| - **padj:** Adjusted p-value for multiple testing using Benjamini and Hochberg method. | |
| ### EnrichR Files | |
| EnrichR is used for gene set enrichment querying four common libraries: KEGG, GO, Wiki Pathways, and ChEA. | |
| Note: EnrichR is not run for salmon outputs. | |
| Example EnrichR file: | |
| | Database | Term | Overlap | P-value | Adjusted-P-value | Combined Score | Genes | | |
| |-----------|-----------------------------------|---------|---------|------------------|----------------|--------------------------------------------------| | |
| | GO_Biological_Process_2021 | mRNA processing (GO:0006397) | 69/190 | 5.48E-22 | 2.21E-18 | 485.4247 | PUS1,PUS3,ATRX,DDX6,ZGRF1,ABCF2,ZNF148,RPL5,PUM1 | | |
| More info on EnrichR can be found [here](https://enrichr.maayanlab.cloud/). | |
| ## FAQ | |
| ### What are the salmon results? | |
| Salmon uses a different alignment algorithm, mapping reads at the transcript level rather than whole gene. | |
| ### Why do I not see enrichR results? | |
| There must be at least 50 differentially expressed genes for EnrichR. | |
| ### Why is my RNASeq data showing a weak knockdown of my gene of interest despite being validated with qRT-PCR? | |
| Discrepancies may arise due to alignment of a non-functional transcript. Viewing aligned files in a Genome Browser may help. | |
| ### Can I remove a sample from the analysis? | |
| It is recommended not to remove samples based on clustering alone, unless there is clear experimental reasoning. | |
| ### Can the GRC re-analyze my RNA-Seq experiment? | |
| Use the BulkDeSeq application in HyperGen, a custom no-code genomics analytics software. | |
| ### What counts files do I use and where? | |
| Use the `deSeq2_counts.txt` files within HyperGen BulkDeqSeq application. | |
| For Gene Set Enrichment Analysis (GSEA), use the `deSeq2_NormCounts.txt` files. Guide to get started: [GSEA Guide](https://www.protocols.io/view/gene-set-enrichment-analysis-kqdg3x67qgq25/v1) | |
| ## Further Educational Resources | |
| - [Genomics Biology Article](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8) | |
| - [DGE Workshop Lesson](https://hbctraining.github.io/DGE_workshop/lessons/04_DGE_DESeq2_analysis.html) | |
| **endofoutput** | |
| ``` |