Example Folder Structure

We return the analysis output files via an SFTP server. For differential gene expression analysis, the structure within your SFTP data folder will follow the general format below.

-Project ID
|--project_id_overview.pdf
|--1.fastq
  |--sample1_S01_L001_R1_001.fastq.gz
  |--sample1_S01_L001_R2_001.fastq.gz
  |--etc.
|--2.sequencing.qc
  |--multiqc_report.html
  |--fastqc
    |--sample1_S01_L001_R1_001_fastqc.html
    |--sample1_S01_L001_R1_001_fastqc.zip
    |--sample1_S01_L001_R2_001_fastqc.html
    |--sample1_S01_L001_R2_001_fastqc.zip
    |--etc.
  |--multiqc_data
    |--multiqc_citations.txt
    |--multiqc_data.json
    |--multiqc_fastqc.txt
    |--multiqc_general_stats.txt
    |--multiqc_software_versions.txt
    |--multiqc_sources.txt
    |--multiqc.log
|--3.alignment-and-counts
  |--CPM.txt
  |--deseq2_normalized_counts.txt
  |--gene_count_matrix.csv
  |--gene_fpkm.tsv
  |--gene_tpm.tsv
  |--STAR_QC_Errors.png
  |--STAR_QC_Reads.png
  |--STAR_Stats.csv
  |--transcript_count_matrix.csv
  |--transcript_fpkm.tsv
  |--transcript_tpm.tsv
  |--bams
    |--sample1_STARAligned.sortedByCoord.out.bam
    |--etc.
|--4.differential-expression
  |--allDEG.heatmap.pdf
  |--MDSplot.edgeR.pdf
  |--PCAplot.deseq.pdf
  |--PCAplot.noiseq.pdf
  |--top50genes.edgeR.heatmap.pdf
  |--top50genes.deseq.heatmap.pdf
  |--clustering
    |--clustered.heatmap.pdf
    |--clusters-by-samples.pdf
    |--genes-in-cluster.txt
    |--sumSquares.pdf
  |--group1_vs_group2 (one folder for each group comparison)
    |--group1_vs_group2.deg.down.venn.minLFC0.png
    |--group1_vs_group2.deg.up.venn.minLFC0.png
    |--group1_vs_group2.deg.down.venn.minLFC1.png
    |--group1_vs_group2.deg.up.venn.minLFC1.png
    |--group1_vs_group2.deg.down.venn.minLFC2.png
    |--group1_vs_group2.deg.up.venn.minLFC2.png
    |--group1_vs_group2.deseq.MAplot.pdf
    |--group1_vs_group2.deseq.volcano.png
    |--group1_vs_group2.edgeR.MAplot.pdf
    |--group1_vs_group2.noiseq.explot.pdf
    |--group1_vs_group2.noiseq.MDplot.pdf
    |--deseq-lists
      |--group1_vs_group2.deg.all.deseq.txt
      |--group1_vs_group2.deg.down.deseq.txt
      |--group1_vs_group2.deg.up.deseq.txt
    |--edgeR-lists
      |--group1_vs_group2.deg.all.edgeR.txt
      |--group1_vs_group2.deg.down.edgeR.txt
      |--group1_vs_group2.deg.up.edgeR.txt
    |--noiseq-lists
      |--group1_vs_group2.deg.all.noiseq.txt
      |--group1_vs_group2.deg.down.noiseq.txt
      |--group1_vs_group2.deg.up.noiseq.txt
    |--merged-deglists
      |--group1_vs_group2.deg.down.minLFC0.csv
      |--group1_vs_group2.deg.up.minLFC0.csv
      |--group1_vs_group2.deg.down.minLFC1.csv
      |--group1_vs_group2.deg.up.minLFC1.csv
      |--group1_vs_group2.deg.down.minLFC2.csv
      |--group1_vs_group2.deg.up.minLFC2.csv
|--5.functional-enrichment
  |--group1_vs_group2 (one folder for each group comparison)
    |--go-enrichment
      |--go.cp.down.barplot.group1_vs_group2.pdf
      |--go.cp.down.cnetplot.group1_vs_group2.pdf
      |--go.cp.down.dotplot.group1_vs_group2.pdf
      |--go.cp.down.emapplot.group1_vs_group2.pdf
      |--go.cp.up.barplot.group1_vs_group2.pdf
      |--go.cp.up.cnetplot.group1_vs_group2.pdf
      |--go.cp.up.dotplot.group1_vs_group2.pdf
      |--go.cp.up.emapplot.group1_vs_group2.pdf
      |--go.group1_vs_group2.down.sig.csv
      |--go.group1_vs_group2.up.sig.csv
    |--kegg-pathways (only for organisms with KEGG pathway data available)
      |--hsa#####.group1_vs_group2.png (one for each significantly enriched pathway)
      |--kegg.group1_vs_group2.clusterProfiler.sig.csv

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Next installment in differential gene expression deliverables: Sequence Processing and Alignment