Immunotherapy is a promising cancer treatment method, but only a few patients benefit from it. Developing new immunotherapy strategies and effective biomarkers of response and resistance is urgent. Recent high-throughput bulk and single-cell gene expression profiling technologies have generated valuable resources in these regards. However, these resources are not well organized and systematic analysis is difficult. Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with immunotherapy clinical outcome and 11,057 tumor/normal samples without immunotherapy clinical outcome, as well as single-cell transcriptome data of 2,116,945 immune cells of 655 samples. TIGER provides many useful modules to analyze the collected data and user-provided data. Using the resource in TIGER, we identified a tumor enriched subset of CD4+ T cells. Melanoma patients with higher signature score of this subset have significantly better response and survival under immunotherapy. We believe that TIGER will be helpful for understanding anti-tumor immunity mechanisms and discovering effective biomarkers. TIGER is freely accessible at http://tiger.canceromics.org/.