Sequence data, analyses, and resources related to the ultra-deep sequencing of the AML31 tumor, relapse, and matched normal.

Sequence Data




This website is maintained as a GitHub repository here.

Almost 3 terabases of sequence data was produced from the tumor samples of a single AML case, including >300x whole genome coverage of the primary tumor sample.

These data are archived in dbGaP under accession id phs000159. An inventory of submitted files is available here: AML31_DBGAP_Submission_Info.xlsx. For further details refer to the sequence page.

Citation: Malachi Griffith*, Christopher A. Miller*, Obi L. Griffith, Kilannin Krysiak, Zachary L. Skidmore, Avinash Ramu, Jason R. Walker, Ha X. Dang, Lee Trani, David E. Larson, Ryan T. Demeter, Michael C. Wendl, Joshua F. McMichael, Rachel E. Austin, Vincent Magrini, Sean D. McGrath, Amy Ly, Shashikant Kulkarni, Matthew G. Cordes, Catrina C. Fronick, Robert S. Fulton, Christopher A. Maher, Li Ding, Jeffery M. Klco10, Elaine R. Mardis, Timothy J. Ley, Richard K. Wilson. Optimizing Cancer Genome Sequencing and Analysis. Cell Systems.