Additional file 2 of Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods

Additional file 2: Table S1. Reported statistic and associated p-value from each combination of pairwise comparison of results between SpatialDE, SPARK-X, scGCO and Squidpy when reported p-values were compared using the Wilcoxon signed rank test. Table S2. Sensitivity and specificity of Squidpy, SPARK-X, SpatialDE and scGCO when used to analyse both simulated datasets generated with SRTsim. Sensitivity and specificity are reported over a range of q-value cut-offs, from 0.01-1.0. Table S3. Packages included for identification of SVGs in benchmarking study. The packages are ordered by assumptions made on distribution of gene expression. The rows highlighted in blue indicate grouped packages using graph-based methods. Table S4. Overview of publicly available 10X Visium datasets to be included in benchmarking process. FF indicates tissues that are fresh frozen and FFPE indicates tissues that are formalin-fixed paraffin-embedded. The filtered output files and imaging data from the Space Ranger v1.0.0, v1.2.0 or V1.3.0 pipeline were downloaded for each dataset.