To use the portal, you will first need to register for an account. Registration is free and open to anyone.
Once registered, you will be sent a confirmation email to activate your account.

Submitting a file

1 | Prepare a Segmentation File

The copy number data (in log2 values) can be generated by any standard platform, including SNP arrays, aCGH, DNA sequencing or RNA sequencing. Please note that the CCLE copy number data against which your data will be compared, is based on Affymetrix SNP6.0 arrays. Regardless of how copy number data are obtained, they should be converted to a segmentation file in the supported formats:
  • Standard Seg File: includes the following columns: Sample_ID, Chromosome, Start_position, End_position, Num_Probes, and Segment_Mean. Example
  • iChorCNA Seg File: generated by the freely available iChorCNA tool; includes the following columns: Sample_ID, Chromosome, Start_position, End_position, Num_Probes, Segment_Median, Copy_number, Call, and Subclone_Status. Example

2 | Fill out form

  • Name of your strain: a unique sample_ID for your uploaded sample
  • Description: a description of your sample (optional)
  • Primary tumor site: select the appropriate primary tumor site for your cell line
  • Reference cell line: select the appropriate cell line from the menu of CCLE lines associated with the primary tumor site that you have selected
  • Log2 CN ratio threshold: specify a single value that will be translated to upper (+) and lower (-) thresholds. Currently this value is hard-coded to 0.3 to enable easy comparison of results across samples of the same cell line.
  • Seg file format: specify whether your segmentation file is a Standard or iChorCNA seg file.
  • Choose and upload file

3 | Submit.

Upon submission of a strain, the segmentation file is validated, and a workflow is run in FireCloud to measure the discordance of the strain with its reference Cell Line. (Storage and compute costs are covered by the Firecloud portal).

Interpreting your results

Your results can be found in the “View My Strains” tab approximately 1-2 minutes from submission and it will include:.
  • Fraction of the genome with CN discordance
  • Pearson’s R value: the correlation between the uploaded copy-number values and those of the matched CCLE line
  • Copy number plots: these plots may be viewed in the portal and downloaded as PDFs. Three copy number plots are provided: the plot of the uploaded sample, the plot of the reference cell line, and the plot of the differences between the first two plots.
The following representative results are based on the MCF7 seg file provided above. Click on view to display sample Copy Number Plots.
Name Description Ref Cell Line Status Fraction of Genome
with CN Discordance
Pearson's r Copy Number Plots
MCF7-P-Standard-Seg Strain P of MCF7 Cell Line MCF7 Complete 0.1707 0.8686 view
The interpretation of discordance values depends on the particular experiments and analyses for which data were generated in the first place. Based on our comprehensive analysis with multiple strains of the MCF7 cell line, the genetic distance between strains is highly correlated with their gene expression and drug response distances. A CN discordance value of less than 0.1 represents closely related strains, whereas a CN discordance value > 0.3 represents remote strains that are likely to differ in their drug sensitivity. Therefore, whenever CN discordance values are > 0.3, it is highly recommended to validate any genomic feature of interest —that is, not to assume that a given genomic feature of the CCLE reference strain applies to your strain as well.


Human cancer cell lines are the workhorse of cancer research. While cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. We recently reported the genomic analyses of 106 cell lines grown in two laboratories revealed extensive clonal diversity. Follow-up comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Importantly, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single cell-derived clones demonstrated that ongoing instability quickly translates into cell line heterogeneity. Testing of the 27 MCF7 strains against 321 anti-cancer compounds uncovered strikingly disparate drug response: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origin and consequence of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.

Cell STRAINER (STRAin INstability profilER) is a web portal designed to assess the discordance between a given cell line sample to its reference sample, as was characterized by the Cancer Cell Line Encyclopedia (CCLE). Users can upload cell line copy number data to assess their strain’s genetic distance from the CCLE reference strain. This genetic distance is a good indicator of gene expression and drug response distances.


When using this website for your scientific work, please cite this portal ( and the following papers:
Jordi Barretina, Giordano Caponigro, Nicolas Stransky, Kavitha Venkatesan, Adam A. Margolin, Sungjoon Kim, Christopher J. Wilson, Joseph Lehár, Gregory V. Kryukov, Dmitriy Sonkin, Anupama Reddy, Manway Liu, Lauren Murray, Michael F. Berger, John E. Monahan, Paula Morais, Jodi Meltzer, Adam Korejwa, Judit Jané-Valbuena, Felipa A. Mapa, Joseph Thibault, Eva Bric-Furlong, Pichai Raman, Aaron Shipway, Ingo H. Engels, Jill Cheng, Guoying K. Yu, Jianjun Yu, Peter Aspesi, Melanie de Silva, Kalpana Jagtap, Michael D. Jones, Li Wang, Charles Hatton, Emanuele Palescandolo, Supriya Gupta, Scott Mahan, Carrie Sougnez, Robert C. Onofrio, Ted Liefeld, Laura MacConaill, Wendy Winckler, Michael Reich, Nanxin Li, Jill P. Mesirov, Stacey B. Gabriel, Gad Getz, Kristin Ardlie, Vivien Chan, Vic E. Myer, Barbara L. Weber, Jeff Porter, Markus Warmuth, Peter Finan, Jennifer L. Harris, Matthew Meyerson, Todd R. Golub, Michael P. Morrissey, William R. Sellers, Robert Schlegel & Levi A. Garraway. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 2012 March 28, 483:603–607. doi:10.1038/nature11003
Uri Ben-David, Benjamin Siranosian, Gavin Ha, Helen Tang, Yaara Oren, Kunihiko Hinohara, Craig A. Strathdee, Joshua Dempster, Nicholas J. Lyons, Robert Burns, Anwesha Nag, Guillaume Kugener, Beth Cimini, Peter Tsvetkov, Yosef E. Maruvka, Ryan O’Rourke, Anthony Garrity, Andrew A. Tubelli, Pratiti Bandopadhayay, Aviad Tsherniak, Francisca Vazquez, Bang Wong, Chet Birger, Mahmoud Ghandi, Aaron R. Thorner, Joshua A. Bittker, Matthew Meyerson, Gad Getz, Rameen Beroukhim & Todd R. Golub. Genetic and Transcriptional Evolution Alters Cancer Cell Line Drug Response. Nature Online 2018 August 08. doi:10.1038/s41586-018-0409-3.