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We provide in-depth, engaged assistance with analysis and interpretation of informatics data sets, design of computational pipelines, and development of new algorithms to drive distillation of biological knowledge from complex data.
APPROACH
APPROACH
Advances in single cell technologies have led to rapid generation of large biological data sets which require informatics approaches to analyze. Single cell resolution of -omics data sets holds tremendous promise for advancing swaths of biology but to fully utilize the data sets, marriage of biological and computational knowledge is required. We believe that this kind of transdisciplinary work requires a firm partnership with constant interaction, which we seek to develop with our clients. We combine our expertise in explaining results and translating biological questions into computational pipelines with dedication and involvement in each project to bring top tier analysis to all of our clients.
EXAMPLE SERVICES
EXAMPLE SERVICES
Single Cell RNA Sequencing
Single Cell RNA Sequencing
Experimental design for single cell RNA sequencing including technology selection, hashing, power analysis, and coordiation with local facilities for library construction and sequencing parameters
Alignment including custom genome annotations and other preprocessing necessary for 10X, BioRad, Parse, and homebrew techniques like SmartSeq2, DropSeq, inDrop, and SeqWell
Sample level quality control including examination of sequencing quality and visualization and filtering of UMI count, feature count, and mitochondrial gene content
Batch quality control and batch effect correction if applicable
Clustering with visualization of marker genes and differentially expressed genes for cluster identification
Differential expression and gene set analyses for all comparison groups of interest
RNA velocity and pseudotime analyses including visualization of velocities, construction of pseudotime trajectories, and identification of genes driving differentiation by trajectory
Customized intercellular signaling analysis linking transcriptional changes with putative signaling pathways.
Data set specific analyses such as copy-number variation, transfer learning, and gene regulatory network analysis
Generation of files and instructions for interactive data viewing with the CellXGene platform.
See a complete example of the types of the analyses you can expect.
Spatial transcriptomics
Spatial transcriptomics
All services available for single cell RNA sequencing as presented above
Region of interest selection and downstream analyses (these can include ANY services available for single cell RNA sequencing as well)
Label transfer to identify spots enriched for specific clusters identified from other single cell RNA sequencing data sets
Intercellular Signaling Analyses
Intercellular Signaling Analyses
We offer a customized, in-house intercellular signaling package based on Domino, a previously published software package developed by our founder and the only scRNAseq intercellular signaling packages capable of identifying ligand-receptor pairs and their transcription factor targets. The package is applicable to single cell RNA sequencing, spatial transcriptomics, and high-sample bulk RNA sequencing data sets.
Global inter-group signaling overview quantifying all estimated intercellular signaling between groups
Visualization of top ligand-receptor-transcription factor pathways between each specific pair of groups
Activation and expression of each ligand, receptor, and transcription factor
Bulk RNA Sequencing
Bulk RNA Sequencing
Power calculations, experimental planning, and coordination with your local core facility or sequencing service provider for improved turn-around times.
Quality control and visualization of raw data
Alignment including custom genome annotations where necessary
Sample and batch level quality control including visualization and filtration on number of reads, proportion of reads aligning to the transcriptome, and correlation and PCA based outlier identification
Differential expression and gene set analyses accounting for complex experimental design, clinical data, and/or batch effect issues if present
Cell type deconvolution to estimate cellular composition of samples
Data set specific analyses such as copy number variation, TCR repertoire estimation, repeat element expression, and others.
Chromatin accessibility assays
Chromatin accessibility assays
Power calculations and experimental design including selection of appropriate experimental assay and coordination with your local core facility or sequencing service provider for improved turn-around times.
Quality control of raw data including adapter trimming, identification of duplicate reads, and sequence-level quality control
Alignment including custom genome generation where necessary
Identification of consensus peaks from biologically replicated data
Comparison of overlapping peaks and differential coverage analysis between interesting experimental groups
Peak annotation and subsequent gene set analyses to determine differentially covered pathways between groups or conditions
Motif identification and visualization
Generation of bed and bigWig files for interactive visualization of peaks using Interactive Genome Viewer, the UCSC genome browser or similar
ABOUT US
ABOUT US
Christopher Cherry is founder and owner of C M Cherry consulting. He holds a PhD from Johns Hopkins University in Biomedical Engineering. He has independently analyzed large multiomic data sets including single cell and bulk RNA sequencing, spatial transcriptomic, whole genome and exome sequencing, chromatin accessibility, TCR sequencing, and clinical correlative data.
Michael Patatanian is a bioinformatic analyst at C M Cherry Consulting. He holds an MPH from the Johns Hopkins Bloomberg School of Public Health, specializing in Biostatistical and Epidemiological methods. In addition to managing client projects, he aids in the analysis and interpretation of single cell and bulk RNA sequencing, and chromatin accessibility datasets.
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