A method for selecting a treatment option for an activated B cell-like diffuse large B cell lymphoma (ABC DLBCL) subject, a germinal center B cell-like diffuse large B cell lymphoma (GCB DLBCL) subject, a primary mediastinal B cell lymphoma (PMBL) subject, a Burkitt lymphoma subject, or a mantle cell lymphoma subject comprising the steps of: (a) isolating a gene expression product from a biopsy sample from a lymphoma subject; (b) obtaining digital gene expression data from the isolated gene expression product, wherein the digital gene expression data comprises data for genes in a gene expression signature, and wherein the gene expression signature comprises at least one of the genes listed in Table 2; (c) optionally obtaining digital gene expression data from a first and second reference set of probes, the second reference set of probes known for classifying ABC DLBCL, GCB DLBCL, PMBL, BL, or MCL; (d) generating a weighted average of the expression levels of genes from the gene expression signature to thereby obtain a gene expression signature value; (e) calculating a predictor score based on the gene expression signature value using the equation: y i = log 2 x i − ∑ j log 2 x j h j − log 2 r i + log 2 g i wherein y i is a predictor score, x i is the counts for gene i for probe set i, probe set i is of the sample being tested, x j is the counts for gene j for probe set j, probe set j is the set of normalization genes of the sample being tested, h j is the normalization weight for probe set j as listed in Table 4, r i is the counts for gene i for probe set i on the first reference set of probes, and g i is the counts for gene i for probe set i on the second reference set of probes, the mathematical terms with r i and g i being equal to zero if no digital gene expression data is obtained from a first and second reference set of probes; (f) classifying the subject as belonging to one of the following groups based on the predictor score of (e): (i) ABC DLBCL, (ii) GCB DLBCL, (iii) PMBL, (iv) BL, or (v) MCL; (g) selecting a treatment option for the subject based on the subject's classification in (f); (a) isolating a gene expression product from a biopsy sample from a lymphoma subject; (b) obtaining digital gene expression data from the isolated gene expression product, wherein the digital gene expression data comprises data for genes in a gene expression signature, and wherein the gene expression signature comprises at least one of the genes listed in Table 2; (c) optionally obtaining digital gene expression data from a first and second reference set of probes, the second reference set of probes known for classifying ABC DLBCL, GCB DLBCL, PMBL, BL, or MCL; (d) generating a weighted average of the expression levels of genes from the gene expression signature to thereby obtain a gene expression signature value; (e) calculating a predictor score based on the gene expression signature value using the equation: y i = log 2 x i − ∑ j log 2 x j h j − log 2 r i + log 2 g i wherein y i is a predictor score, x i is the counts for gene i for probe set i, probe set i is of the sample being tested, x j is the counts for gene j for probe set j, probe set j is the set of normalization genes of the sample being tested, h j is the normalization weight for probe set j as listed in Table 4, r i is the counts for gene i for probe set i on the first reference set of probes, and g i is the counts for gene i for probe set i on the second reference set of probes, the mathematical terms with r i and g i being equal to zero if no digital gene expression data is obtained from a first and second reference set of probes; (f) classifying the subject as belonging to one of the following groups based on the predictor score of (e): (i) ABC DLBCL, (ii) GCB DLBCL, (iii) PMBL, (iv) BL, or (v) MCL; (g) selecting a treatment option for the subject based on the subject's classification in (f);