fbpx
Contacts
Whatsapp Us
Close
Contacts

Building No, 62, Block C2 Block C 2 Gulberg III, Lahore

(332) 252-3640

[email protected]

RNA Seq Data Analysis

RNA Seq Data Analysis

Comprehensive RNA-Seq Analysis Services

At Life Seq Data, we offer complete RNA-Seq analysis services, from data collection and preprocessing to advanced differential expression analysis and functional enrichment. Our team of experts ensures high-quality and reliable results, supporting researchers worldwide in uncovering the complexities of gene regulation and expression.

Our Services:

  • Trimming and Mapping of Reads: Align reads to the reference genome or transcriptome.
  • Aligned Data Provision: Provide BAM/SAM files for read quantification.
  • De-Multiplexed Aggregated Data: Supply Picard BAM files with summary metrics.
  • De Novo Transcriptome Assembly: Construct transcriptomes from RNA-Seq data without a reference genome.
  • Transcript and Isoform Detection: Identify various transcripts and their isoforms.
  • RNA SNP/INDEL Detection: Discover single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs) in RNA sequences.
  • Differential Expression Analysis: Conduct analysis of genes, isoforms, and exons to find differentially expressed elements.
  • DGE Results Provision: Supply CSV files with differential gene expression results.
  • Differential Splicing Analysis: Perform DEXSeq report for alternative splicing events.
  • Gene Fusion Discovery: Identify novel gene fusions.
  • Novel Transcript Discovery: Discover previously unannotated transcripts.
  • Fusion Genes, Circular RNAs, and Trans-Splicing Events Analysis: Analyze complex RNA structures and events.
  • Differentially Expressed Non-Coding RNAs Identification: Identify non-coding RNAs with differential expression.
  • Differentially Expressed miRNAs Identification: Detect miRNAs with differential expression.
  • Functional Enrichment Analysis: Analyze gene sets for enrichment in biological pathways and functions.
  • Quality Control Using Fastp: Ensure high-quality RNA-Seq data.
  • Protein-Protein Interaction (PPI) Using STRING: Explore interactions between proteins.
  • PCA Plot Normalization: Visualize differential gene expression.

RNA-Sequencing

RNA-Seq is a powerful next-generation sequencing (NGS) method for identifying genes and pathways underlying diseases or conditions. Over the past decade, RNA-Seq has become indispensable for transcriptome-wide analysis of differential gene expression and splicing. It offers numerous advantages over traditional microarray technology.

RNA-Sequencing Data Analysis

RNA sequencing data analysis emphasizes the intricate mechanisms of gene regulation. By examining the transcriptome, RNA-Seq data reveals which genes are active or inactive and to what extent. This comprehensive analysis addresses countless research questions across biology and biomedicine.

RNA-Sequencing Analysis Pipeline

Data Retrieval

  • Start with finding the required dataset in BAM or FASTQ format from sources like Array Express, GEO-NCBI, or EMBL-ENA.
  • Perform analysis on in-house sequenced data as well.

Quality Control

  • Use tools like FASTQC and Trim Galore to preprocess data, ensuring removal of low-quality reads and contaminants.

Read Mapping/Alignment

  • Align sequence reads to a reference genome or assemble de novo using tools like HISAT2, STAR, and BowTie2.

Assembly and Read Quantification

  • Assemble reads into a transcriptome and quantify gene expression using StringTie and HT-Seq.

Differential Gene Expression Analysis

  • Perform statistical analysis on normalized read count data to discover changes in gene expression between experimental groups using DESeq2, edgeR, and Ballgown.

Functional Enrichment Analysis

  • Determine classes of genes or proteins that are over-represented in gene sets and related to disease phenotypes using topGo, enrichR, and ClusterProfiler.

Protein-Protein Interaction

  • Use STRING database to analyze interactions between differentially expressed genes.

Network Analysis

  • Generate and analyze networks of differentially expressed genes to identify regulatory relationships and functional pathways using Cytoscape.

Linux and R Integration

  • Perform the entire analysis using Linux and R with custom scripts for efficient RNA-Seq pipeline automation.

At Life Seq Data, our RNA-Seq analysis services offer comprehensive support for your research, from initial data collection to advanced bioinformatics analysis. With our expertise and state-of-the-art tools, we help you uncover the complexities of gene regulation and expression, driving forward your scientific discoveries.