T

transcriptomics

Bulk RNA-seq differential expression analysis of three tissues: brain, colon and lung

Single cell RNA-seq differential expression analysis of somato-sensory cortex

StCsm next-generation sequencing data processing Nextflow pipeline.

StCsm sequencing data analysis in R programming language.

This project is a comparison between two development stages in berry (Véraison and mature) and typical abiotic stress treatments (ABA-treated and Polyol-treated). After RNA-sequencing (TruSeq Stranded mRNA cDNA libraries, ~ 600 ng of berry total RNA) about 70 million paired-end reads of 50 bp were produced per sample. Principal component and pairwise comparisons based on ANOVA-like approach of edgeR were used to identify the differentially expressed genes (DEG) in these four groups of samples.

The last version of Vitis vinifera reference geneme was used for the alignment (https://integrape.eu/resources/genes-genomes/genome-accessions/).

NOTE// SIMPLE DEG ANALYSIS): In order to perform a global analysis of expression, not subject to sequence analysis 50 bp paired end reads is better than 100 bp single end reads. Why? 50 base-pair paired-end reads span a longer region of the transcript. Each read represents one end of a ~200-300 base-pair RNA fragment, compared to a 100 base-pair read which only gives you information about 100 bases. A larger fragment means you are more likely to span a splice junction, insertion, or deletion. Therefore 50 bp is preferable. Remember that with next gen sequencing technology, for the most part your read is only a "tag" that tells you where in the genome the fragment originated. As long as the "tag" is long enough to be unique (and 50 bp is for the most part) you are set.

eXploring the Transcriptomes of Bronchial LEsions

batch data download from Genbank or RefSeq