Bioinformatics and Genomics core-lab (BGcore)

Bioinformatics and Genomics core-lab (BGcore)

The Bioinformatics and Genomics core-lab (BGcore) is a service facility dedicated to provide support to internal and external researcher on the generation and analysis of genomics/transcriptomics high-throughput data. Specifically, BGcore has a deep experience in “difficult” samples handling and provides a full support to researcher from experimental design to data mining [1-9].

Sequencing libraries are prepared at MBC and are run on NextSeq 500, available at MBC, as part of the open-lab instruments of the University of Turin. For whole genome studies BGcore has access to the NovaSeq at IIT in Genova. Data generated by the sequencers are analyzed on C3S (HPC center of University of Turin) machines using dedicated workflows developed by us [10-15].

The Bioinformatics and Genomics core-lab (BGcore) is directed by Prof. Raffaele A Calogero, which has a multi-years’ experience in the area of bioinformatics and transcriptomics. Prof. Calogero is also the co-founder of reproducible Bioinformatics Project, a community devoted to the development of robust and reproducible data analysis workflows.


Experimental design

BGcore provides a support session for experimental design free of charge, usually about 4 hours meeting with researcher in which BGcore gets into the experimental question to be addressed by genomics/transcriptomics studies. Then, BGcore provides within three days from the meeting a proposal for an optimal experimental design. Within other three days BGcore meets with the researcher to refine the experiment design.





Library preparation

The cost of a library preparation is affected by the type of kit to be used, sequencing depth and number of samples to be run (for a quote please inquire to

Supported protocols:

  • Any bulk RNA-seq,  
  • circRNA-seq,
  • extracellular vesicles transcriptome characterization (coding, non-coding transcripts, miRNAs)
  • single-cell spatial transcriptomics (visium platform, 10XGenomics)
Bioinformatics analysis
  • The conversion of BCL files in fastq and the conversion in counts/TPM/FPKM is free of charge.
  • On the basis of the experimental design is estimated the number of working hours to be dedicated to the analysis (for a quote please inquire to
  • As part of the bioinformatics support, BGcore provides data storage up to 1 Tb or delivers the overall data in a hard disk (for a quote please inquire to
  • BGcore also provides all parts done by the facility as ready to go material and methods to be used for publication, free of charge.

Supported analyses:

  • From fastq to differential expression analysis for any bulk RNAseq experiment.
  • Data mining for differentially expressed genes, e.g. multi-omics data integration, GSEA, genes regulatory networks detection.
  • Single-cell data analysis and mining, any platform.
  • circRNA data analysis.
  • Custom bioinformatics workflows, e.g.  deep learning approaches to detect gene regulatory networks, multi-omics/phenotype relationship, etc..

For information:


Prof. Raffaele A. Calogero

  • Bioinformatics and Genomics Unit
  • Dipartimento di Biotecnologie e Scienze della Salute
  • Via Nizza 52, Torino 10126
  • tel. ++39 0116706454
  • Fax ++39 0112366454
  • Mobile ++39 3333827080
  • email:
  • raffaele[dot]calogero[at]gmail[dot]com


  1. Rodriguez-Fraticelli AE, Wolock SL, Weinreb CS, Panero R, Patel SH, Jankovic M, Sun J, Calogero RA, Klein AM, Camargo FD: Clonal analysis of lineage fate in native haematopoiesis. Nature 2018, 553(7687):212-216.
  2. uan WC, Pepe-Mooney B, Galli GG, Dill MT, Huang HT, Hao M, Wang Y, Liang H, Calogero RA, Camargo FD: NUAK2 is a critical YAP target in liver cancer. Nat Commun 2018, 9(1):4834.
  3. Quaglino E, Rolla S, Iezzi M, Spadaro M, Musiani P, De Giovanni C, Lollini PL, Lanzardo S, Forni G, Sanges R et al: Concordant morphologic and gene expression data show that a vaccine halts HER-2/neu preneoplastic lesions. The Journal of clinical investigation 2004, 113(5):709-717.
  4. Deregibus MC, Cantaluppi V, Calogero R, Lo Iacono M, Tetta C, Biancone L, Bruno S, Bussolati B, Camussi G: Endothelial progenitor cell derived microvesicles activate an angiogenic program in endothelial cells by a horizontal transfer of mRNA. Blood 2007, 110(7):2440-2448.
  5. Cavallo F, Calogero RA, Forni G: Are oncoantigens suitable targets for anti-tumour therapy? Nature reviews Cancer 2007, 7(9):707-713.
  6. Berkofsky-Fessler W, Buzzai M, Kim MK, Fruchtman S, Najfeld V, Min DJ, Costa FF, Bischof JM, Soares MB, McConnell MJ et al: Transcriptional profiling of polycythemia vera identifies gene expression patterns both dependent and independent from the action of JAK2V617F. Clinical cancer research : an official journal of the American Association for Cancer Research 2010, 16(17):4339-4352.
  7. Galli GG, Honnens de Lichtenberg K, Carrara M, Hans W, Wuelling M, Mentz B, Multhaupt HA, Fog CK, Jensen KT, Rappsilber J et al: Prdm5 regulates collagen gene transcription by association with RNA polymerase II in developing bone. PLoS genetics 2012, 8(5):e1002711.
  8. Tremblay AM, Missiaglia E, Galli GG, Hettmer S, Urcia R, Carrara M, Judson RN, Thway K, Nadal G, Selfe JL et al: The Hippo transducer YAP1 transforms activated satellite cells and is a potent effector of embryonal rhabdomyosarcoma formation. Cancer cell 2014, 26(2):273-287.
  9. Christodoulou C, Spencer JA, Yeh SA, Turcotte R, Kokkaliaris KD, Panero R, Ramos A, Guo G, Seyedhassantehrani N, Esipova TV et al: Live-animal imaging of native haematopoietic stem and progenitor cells. Nature 2020, 578(7794):278-283.
  10. Beccuti M, Cordero F, Arigoni M, Panero R, Amparore EG, Donatelli S, Calogero RA: SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer. Bioinformatics 2017.
  11. Kulkarni N, Alessandri L, Panero R, Arigoni M, Olivero M, Ferrero G, Cordero F, Beccuti M, Calogero RA: Reproducible bioinformatics project: a community for reproducible bioinformatics analysis pipelines. BMC bioinformatics 2018, 19(Suppl 10):349.
  12. Cordero F, Beccuti M, Arigoni M, Donatelli S, Calogero RA: Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis. PloS one 2012, 7(2):e31630.
  13. Beccuti M, Carrara M, Cordero F, Lazzarato F, Donatelli S, Nadalin F, Policriti A, Calogero RA: Chimera: a Bioconductor package for secondary analysis of fusion products. Bioinformatics 2014, 30(24):3556-3557.
  14. Beccuti M, Genuardi E, Romano G, Monitillo L, Barbero D, Boccadoro M, Ladetto M, Calogero R, Ferrero S, Cordero F: HashClone: a new tool to quantify the minimal residual disease in B-cell lymphoma from deep sequencing data. BMC bioinformatics 2017, 18(1):516.
  15. Carrara M, Lum J, Cordero F, Beccuti M, Poidinger M, Donatelli S, Calogero RA, Zolezzi F: Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis. BMC bioinformatics 2015, 16 Suppl 9:S2.