Services for your data-analysis needs.

Transcriptome-wide analysis (bulk RNA-seq) is a powerful approach to measure gene expression within and across samples, conditions, drug-treatments and in disease.

Bulk RNA-seq can identify differentially expressed genes, molecular targets across conditions and characterize splicing variants, isoform usage and novel transcripts for generation of mechanistic hypotheses across cells and tissues.

We can help to design your RNA-seq experiments with overall study design incl. consideration on
(i) controls, number of replicates,
(ii) batch-balanced design,
(iii) type (total-seq vs mRNA-seq)
(iv) sequencing depth among others.

Our analysis packages include complete workflow from data pre-processing (quality control, alignment, quantification) to downstream analysis including exploratory analysis (Principal Component Analysis, Marker heatmaps), differential expression, pathway and gene set enrichment analysis.

We can perform a variety of additional analysis catered to your specific biological questions and goals.

Single-cell RNA-seq (scRNA-seq) enables gene expression measurements within individual cells capturing cellular heterogeneity, cataloguing cellular populations and identification of cell states/types alongside marker gene expression. The scRNA-seq data can be generated from a variety of platforms, technologies and sequencing configurations, including 10x Genomics, Drop-Seq, Smart-seq, combinatorial indexing approaches.

We can help plan, design your scRNA-seq experiment for your research questions, goals and various critical considerations:
(i) sample/tissue type (cells vs nuclei), sample preparation and selection (sorting, enrichment)
(ii) Study design (single vs multi-sample, time-course, perturbation, drug treatment)
(iii) Throughput (number of cells)
(iv) Chemistry and platform (total vs mRNA-seq, coverage (whole transcript, 3' vs 5' tags), platforms (plate-based, droplet, combinatorial indexing)
(v) library and sequencing (vi) Cost (experimental and analysis)

Our analysis packages include end-to-end solutions from upstream analusis (library QC, mapping, alignment) to data QC (cells, genes) and downstream analysis such as pre-processing (scaling, normalization), non-linear dimensionality reduction, clustering/cell type and marker identification. We can perform additional specific analysis suited for your project such as trajectory analysis, pseudo-time, integration with public datasets ligand-receptor inference etc., across conditions, sample groups, perturbation/treatment and disease samples

Spatial Transcriptomics (ST) provides gene expression measurements within tissues preserving the spatial information. The spatial distribution of transcripts and heterogeneity provides a fine-grained view of cellular, multi- and sub-cellular architectures in both cells and tissue level. The ST datasets can be generated from imaging or sequencing based approaches, varying broadly in resolution, throughput and number of captured transcripts (targetted panel vs seq-based).

We can help plan your ST experiment for your specific research questions and key considerations:
(i) Tissue and sample prep (type, thickness etc.,)
(ii) Resolution (single-cell, sub-cellular vs domain level)
(iii) Transcript detection (targetted vs unbiased) and technology
(iv) Cost (experimental and analysis)

We can provide custom solutions for ST analysis including quality control of data, pre- and post-processing and analysis incl. spot & cell-type deconvolution, cell type identification and spatially variable markers. We can perform additional specific analysis suited for your project such as comparison with protein markers, integration with public scRNA-seq and ST datasets.

Individual cell states and responses are collectively coordinated at epigenetic, transcriptional and protein-level.
Each individual modality (Chromatin accessiblity, RNA/transcripts, Proteins) provides a selective view of the overall regulation.

Multi-modal data generation and integration can help understand, interpret your biological questions and provide new directions for research, target identification validation and discovery.

We can provide custom analysis solutions for projects, research questions and goals
(i) data integration across platforms, data-types, conditions (perturbation, drug, disease),
(ii) Identification and analysis of public data
(iii) harmonization and integration with your multi-modal bulk and single-cell data.

The epigenome is associated with array of chromatin modifications, DNA methylation, chromatin conformation that provides a layer of regulation upstream of transcription. We can provide custom analysis solutions for your bulk and single-cell epigenome projects (ATAC-seq, ChIP-Seq, CUT&Tag, scATAC-seq etc.,). Computational Biology & data analysis needs.

We can provide data analysis solutions and support for any other computational biology and data analysis projects and your research goals. We can provide consulting and analysis sppport on case-by-case and capacity basis for short time-aware projects towards publications, data scraping, grants to larger research projects and goals

We can provide data analysis solutions and support for any other computational biology and data analysis projects and your research goals.

We can provide consulting and analysis sppport on case-by-case and capacity basis for short time-aware projects towards publications, data scraping, grants to larger research projects and goals