11932 results for "cancer rna-seq"

in 17.73 milliseconds.

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• MSI-Exome-DAC Team Microsatellites Instability and Cancer, INSERM Hospital Saint-Antoine, Paris 12, France Carte d'identité des tumeurs, French league against cancer, Paris France

  Dac EGAC00001000665

• CLL cancer Sample Sequencing

  CLL cancer Sample Sequencing

  Dataset EGAD00001000004

• Various Cancer Fusion Gene Sequencing

  Various Cancer Fusion Gene Sequencing

  Dataset EGAD00001000005

• Methylation profiles in blood (breast cancer cases)

  Raw methylation data from blood samples in breast cancer cases.

  Dataset EGAD00010002470

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  Study EGAS00001007299

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dac EGAC50000000486

• Long read mRNA sequencing of human neural retinal samples

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Files are raw BAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000101

• Transcriptomic sequencing of early and late passage of mCRC tumoroids

  Dataset of 46 mCRC tumoroids from different passages (23 early-passage 3, 23 late-passage 8-12). FASTQ files of paired sequencing of PolyA-enriched total RNA

  Dataset EGAD50000000153

• RNAseq of samples from CLL patients treated with idelalisib in vivo

  The dataset contains RNA sequencing data from 18 paired samples of 9 CLL patients treated with idelalisib in vivo (median time on therapy 4 weeks; range 2-5 weeks).

  Dataset EGAD50000000878