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When a feature (gene) has low expression, it will be filtered by automatic independent filtering. To avoid this, you can either perform either filter features to exclude low expression features before Deseq2, or in the Deseq2 advanced options, choose apply independent filtering setting. Details about independent filtering can be found at the Deseq2 documentation. 

Click here for troubleshooting other differential analysis models and "?" results

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In Partek Flow, fold change is in linear scale (even if the input data is in log scale). It is converted from ratio, which is the LSmean of group one divided by LSmean of group two in your comparison. When the ratio is greater than 1, fold change is identical to ratio; when the ratio is less than 1, fold change is -1/ratio. There is no fold change value between -1 to 1. When ratio/fold change is 1, it that means there is no change between the two groups.

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You should have at least the following two attributes in the Meta dataMetadata, treatment (including two subgroups) and subject ID (to pair the two samples). When perform performing differential analysis, choose ANOVA and include both attributes into the ANOVA model, the two-way ANOVA is mathematically equivalent to paired t-Test.

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In Partek Flow, GSEA should be performed on a sample/cell and feature matrix data node , (e.g. normalization count data). GSEA is used to detect a gene set/a pathway which is significantly different between two groups. Gene set enrichment should be performed on a filtered gene list; it is used to identify overrepresented gene set/pathway based the filtered gene list using Fisher's exact test. The input data is a filtered list using gene names.

When should I use GSEA or Gene set ANOVA?

Both methods should perform be performed on normalized matrix data node, and requires gene symbol in feature annotation. Both methods are detecting differentially expressed Gene set (pathway) instead of each individual gene.   The algorithms are different. GSEA is a popular method from the Broad institute.  Gene Set ANOVA is based on generalized linear model, here is the are the details.