Overview

When you publish manuscripts based on data generated at our facility, we would greatly appreciate an acknowledgement of our efforts. Please cite our facility as follows (for example):

Basic processing of the raw data were performed by the University of Illinois at Chicago Research Informatics Core (UICRIC).

We adhere to a general policy for acknowledgements and authorship as established by the Association for Biomolecular Resource Facilities (ABRF) , and we support the following statement from the ABRF.

The existence of core facilities depends in part on proper acknowledgment in publications. This is an important metric of the value of most core facilities. Proper acknowledgment of core facilities enables them to obtain financial and other support so that they may continue to provide their essential services in the best ways possible. It also helps core personnel to advance in their careers, adding to the overall health of the core facility.

Please contact us for assistance in drafting manuscripts.

Output Files

File Description Type
genes.txt Raw counts per gene result
exons.zip Raw counts per exon result
exons_annotation.zip Exon-to-gene annotation result
junctions.zip Raw counts per splice junction result
junctions_annotation.zip Junctions-to-gene annotation result
isoforms.zip Raw counts per isoform result
isoforms_annotation.zip Isoform-to-gene annotation result
gene_annotation_summary.txt Summary of read annotations result
genes_norm.txt Normalized gene expression levels (CPM units) result
Sample OriginalID
RNA_mouse_polyA_folB.1 RNA_mouse_polyA_folB.1
RNA_mouse_polyA_folB.2 RNA_mouse_polyA_folB.2
RNA_mouse_polyA_pre-proB.1 RNA_mouse_polyA_pre-proB.1
RNA_mouse_polyA_pre-proB.2 RNA_mouse_polyA_pre-proB.2

Details

Method: cutadapt

Sequencing trimming using cutadapt

Custom Parameters
  • -a = file:/mnt/store3/clustcrilab/reference/adapters/TruSeq_R1.fa
  • -q = 20,20
  • -m = 40
  • --nextseq-trim = 20
  • --report = minimal
Method: Quality trimming

Quality trimming based on quality threshold and length parameters.

Custom Parameters
  • min length = 40
  • p = 20,20
Method: Adapter trimming

Adapter/primer sequences were trimmed from the reads.

Custom Parameters
  • 5' adapter = AGATCGGAAGAGCACACGTCTGAACTCCAGTCA

FiguresReturn to top

Figure 1. Trimming results

TablesReturn to top

Table 1. Trimming statistics Download table data

Sample Raw reads Reads passed trimming Reads dropped Percent passing
RNA_mouse_polyA_folB.1 27890026 22182967 5707059 79.54 %
RNA_mouse_polyA_folB.2 28589327 22844856 5744471 79.91 %
RNA_mouse_polyA_pre-proB.1 28408668 23268450 5140218 81.91 %
RNA_mouse_polyA_pre-proB.2 27189999 22352203 4837796 82.21 %

Details

Method: STAR

Reads were aligned to the reference genome in a splice-aware manner using STAR.

Method: PCR Duplicate Removal with Picard

Apparent PCR duplicates were checked or removed with Picard (note: for RNA-seq samples, the full set of alignments are used for gene expression quantification).

FiguresReturn to top

Figure 1. Alignment results

TablesReturn to top

Table 1. Alignment statistics Download table data

Sample Alignments, duplicates removed Alignments PCR duplicates Unaligned reads Percent aligned Percent non-duplicates
RNA_mouse_polyA_folB.1 9251608 21588988 12337380 593979 97.3 % 41.7 %
RNA_mouse_polyA_folB.2 9663713 22224300 12560587 620556 97.3 % 42.3 %
RNA_mouse_polyA_pre-proB.1 9709200 22608292 12899092 660158 97.2 % 41.7 %
RNA_mouse_polyA_pre-proB.2 9442179 21741704 12299525 610499 97.3 % 42.2 %

Details

Method: BWA MEM

Reads were aligned to the reference genome using BWA MEM.

Reference sequence database : Mouse rRNA

Mouse ribosomal RNA sequences from NCBI and Ensembl

FiguresReturn to top

Figure 1. Filtering results

TablesReturn to top

Table 1. Filtering statistics Download table data

Sample Alignments rRNA sequence counts Unfiltered alignments Percent passing
RNA_mouse_polyA_folB.1 21588988 47404 21541584 99.8 %
RNA_mouse_polyA_folB.2 22224300 37122 22187178 99.8 %
RNA_mouse_polyA_pre-proB.1 22608292 109373 22498919 99.5 %
RNA_mouse_polyA_pre-proB.2 21741704 72023 21669681 99.7 %

Details

Method: FeatureCounts

Abundance of genomic features (e.g., genes) were quantified as raw counts based on read alignments using featureCounts.

Custom Parameters
  • reference = mm10_mRNA.gtf
  • parameters = -t exon -g gene_id --countReadPairs -s 2
Method: FeatureCounts

Abundance of genomic features (e.g., genes) were quantified as raw counts based on read alignments using featureCounts.

Custom Parameters
  • reference = reference_flattened.saf
  • parameters = --countReadPairs -F SAF -O --fraction -f -s 2
Gene annotation database : mm10 Ensembl

Ensembl annotations for mouse genome v.mm10

FiguresReturn to top

Figure 1. Quantification results

Figure 2. PCA plot

TablesReturn to top

Table 1. Data processing summary statistics Download table data

Stats Raw reads Trimmed reads Percent Alignments Percent Alignments, duplicates removed Percent rRNA sequence counts Percent Unassigned_MultiMapping Percent Unassigned_NoFeatures Percent Unassigned_Ambiguity Percent Gene sum Percent Genes expressed (out of 39056) Entropy (base 2) Isoform sum Percent Isoforms expressed (out of 112588) Entropy (base 2) Read length Directions Orientation
RNA_mouse_polyA_folB.1 27890026 22182967 0.795373 21588988 0.774076 9251608 0.331717 47404 0.00169968 10228652 0.366749 3747931 0.134382 157395 0.00564342 14635393 0.524754 17703 11.972 16625215 0.596099 54956 12.844 49 SE Reverse stranded
RNA_mouse_polyA_folB.2 28589327 22844856 0.799069 22224300 0.777364 9663713 0.338018 37122 0.00129846 10084610 0.35274 4352410 0.152239 150550 0.00526595 14711502 0.51458 17760 11.967 16646967 0.582279 54583 12.846 49 SE Reverse stranded
RNA_mouse_polyA_pre-proB.1 28408668 23268450 0.819062 22608292 0.795824 9709200 0.341769 109373 0.00384999 10655117 0.375066 3706145 0.130458 155124 0.00546045 15540809 0.547045 19120 12.213 17785508 0.626059 57891 13.010 49 SE Reverse stranded
RNA_mouse_polyA_pre-proB.2 27189999 22352203 0.822074 21741704 0.799621 9442179 0.347267 72023 0.00264888 10126663 0.372441 3451892 0.126954 153044 0.00562869 15083443 0.554742 19060 12.219 17189354 0.632194 57939 13.022 49 SE Reverse stranded

  • Gene isoform quantification

Details

Method: Kallisto

Gene isoforms were quantified with Kallisto, using k-mer-based pseudo-alignment and expectation maximization to probabilistically assign reads to isoforms.

Reference sequence database : mm10 transcriptome

Mouse mRNA and long-non-coding transcriptome from Ensembl, genome mm10.

Citations