We establish new algorithmic guarantees with matching hardness results for coloring and independent set problems in one-sided expanders and related classes of graphs. For example, given a $3$-colorable regular one-sided expander, we compute in polynomial time either an independent set of relative size at least $1/2-o(1)$ or a proper $3$-coloring for all but an $o(1)$ fraction of the vertices, where $o(1)$ stands for a function that tends to $0$ with the second largest eigenvalue of the normalized adjacency matrix. This result improves on recent seminal work of Bafna, Hsieh, and Kothari (STOC 2025) developing an algorithm that efficiently finds independent sets of relative size at least $0.01$ in such graphs. We also obtain an efficient $1.6667$-factor approximation algorithm for VERTEX COVER in sufficiently strong regular one-sided expanders, improving over a previous $(2-ε)$-factor approximation in such graphs for an unspecified constant $ε>0$. We propose a new stratification of $k$-COLORING in terms of $k$-by-$k$ matrices akin to predicate sets for constraint satisfaction problems. We prove that whenever this matrix has repeated rows, the corresponding coloring problem is NP-hard for one-sided expanders under the Unique Games Conjecture. On the other hand, if this matrix has no repeated rows, our algorithms can solve the corresponding coloring problem on one-sided expanders in polynomial time. As starting point for our algorithmic results, we show a property of graph spectra that, to the best of our knowledge, has not been observed before: The number of negative eigenvalues smaller than $-τ$ is at most $O(1/τ^{4})$ times the number of eigenvalues larger than $τ^{2}/2$. While this result allows us to bound the number of eigenvalues bounded away from $0$ in one-sided spectral expanders, this property alone is insufficient for our algorithmic results.