Bioinformatic Analysis

Bulk RNA-seq

Our standard services include genomic alignments, data quality control and normalization, and identification of differentially expressed genes. 

For RNA-Seq analysis, we offer:

  • FASTQC quality control of raw sequencing reads
  • Alignment to standard reference genome using STAR
  • Gene-level abundance measurements
  • Sample-level unsupervised hierarchical clustering and principle component analysis
  • Differential expression testing for pairwise, group comparisons as well as more complex models (multifactorial, time-series, etc) using DESeq2
  • Integrative Genome Browser based visualization
Analysis Type Features
RNA seq QC: PCA+tSNE+correlation plots demonstrating
clustering between biological replicates
DE: Volcano Plots, MA Plots, gene expression
heat maps showing statistically significant genes showing high fold change
Small-RNA seq QC: PCA+tSNE+correlation plots demonstrating
clustering between biological replicates
DE: Volcano Plots, MA Plots, gene expression
heat maps showing statistically significant genes showing high fold change
ChIP-seq Peak Calling: ChIP-seq peak calling with
Macs2 and ENCODE pipelines
Coverage Graphs: Creation of genome-wide
coverage graphs normalized for sequencing depth
and IP efficiency
QC: PCA+tSNE+correlation plots demonstrating
clustering between biological replicates
DE: Volcano Plots, MA Plots, peak region enrichment
heat maps showing statistically significant regions showing high fold change
Single-cell RNA seq Preprocessing: Support for all data
preprocessing steps for the 10x Genomics Single
Cell platform, including merging of multiple runs
Exploratory Data Analysis: Unsupervised
clustering of cells, identification of cluster
specific gene markers
DE: Identification of differentially
expressed genes between conditions (genotypes,
treatments) within or between clusters
Custom

Stand-alone analysis can be performed
based on the researcher's requirements.
Contact Walter Eckalbar for more info.

 

All analyses are available for download from UCSF's secure Box site. We schedule a meeting at the end of each study to discuss the data analysis in detail.