Proteomics
Olink NPX exports from plasma, serum, or CSF get QC, bridging, differential tables, figures, commented R, and a Methods draft.
| Category | Details |
|---|---|
| Supported platforms / instruments | Olink Target 96; Explore 384 modules (Cardiometabolic, Inflammation, Neurology, Oncology, and II panels); Explore 3072; Explore HT; Focus; Reveal; NPX exports from NPX Manager, NPX Map, and NPX Explore software |
| Input requirements | NPX or QUANT exports (CSV, Excel, Parquet, or ZIP as exported by Olink software); sample manifest with condition, plate/batch, and replicate IDs; bridge samples for multi-batch or multi-project designs (8-64 overlapping samples depending on Olink product pairing; [3]); multiple biological replicates per condition (often ≥3) for variance estimation [5]. Confirmed at kickoff. |
| Reference builds supported | Not genome-based. UniProt accessions per Olink assay panel (OlinkID to UniProt mapping validated via `check_npx` in OlinkAnalyze 5.0+). No GRCh38 or other assembly is required. |
| Primary tools (with versions) | OlinkAnalyze 5.0+; OlinkAnalyzeVignettes; limma 3.60+; clusterProfiler via `olink_pathway_enrichment`; lme4/lmerTest via `olink_lmer`, pinned per project |
| Typical turnaround time | 2-4 weeks (single NPX project, one contrast, standard DE and enrichment); 4-8 weeks (multi-batch bridging, cross-product normalization, mixed models, or large cohorts). Confirmed at kickoff. |
| Deliverable formats | Long and wide NPX matrices (`.csv`, `.tsv`, `.rds`); differential protein tables; PDF/SVG QC, PCA, volcano, and heatmap plots; HTML QC report; commented R scripts; Methods draft |
| Key cited best-practice reference | Olink Proteomics [6], OlinkAnalyzeVignettes bridging tutorials; Assarsson et al. [2], *PLOS ONE* (96-plex PEA validation) |
| Custom / bespoke analysis | Non-standard contrasts, cross-cohort integration, proteogenomic correlation, custom enrichment gene sets, client-specified statistical models, or alternate deliverable formats scoped at kickoff |
Olink PEA analysis imports vendor NPX matrices, checks assay and sample integrity, optionally bridges batches or Olink products, and tests per-protein abundance differences on log₂-scaled NPX values. That measures which targeted proteins change between conditions without peptide identification or spectral library search [2, 3]. Unlike LC-MS discovery proteomics, PEA uses dual-antibody proximity ligation with qPCR or NGS readout on fixed panels [4]. Unlike single-target ELISA, 96-plex panels consume 1 µL per sample [2]. Explore HT measures about 5,400 proteins from 2 µL with about a 10-log dynamic range [3]. Custom workflows are agreed at kickoff. See the Olink proximity extension assay glossary.
Olink PEA fits when you need multiplex measurement of known or candidate proteins in biofluids at low sample volume, for example biomarker panels, pathway monitoring, or genetic-proteomic association, without untargeted MS depth [1].
| Approach | Best for | Limitations | Approximate cost range |
|---|---|---|---|
| Olink PEA (NPX) | Targeted multiplex biomarkers in plasma, serum, or CSF; 96-5,400 proteins; 1-2 µL sample input | Relative NPX quantification; bridging required across batches or products; fixed antibody panels | Moderate per-sample assay cost; moderate bioinformatics |
| LC-MS DDA/DIA | Untargeted proteome discovery, PTMs, novel protein identification | Higher sample volume and MS time; complex missing-value handling | Higher MS acquisition and bioinformatics cost |
| Single-target ELISA | One analyte with an established clinical-grade assay | No multiplex discovery; poor scalability for panels | Lower per analyte; limited for multi-protein signatures |
Pepkio confirms NPX format, panel version, contrast definitions, and bridge-sample plans before import. Confounded batch-by-condition designs, or too few bridge samples for multi-project merging, are flagged at kickoff [3].
Tools used: Custom validation scripts; OlinkAnalyze 5.0+ design checklist
Output: sample_manifest.csv with sample IDs, conditions, plate/batch IDs, bridge flags, and design notes
NPX files load from Olink software exports without manual editing. QUANT exports can be log-transformed when scoped (OlinkAnalyze 5.0+).
Tools used: OlinkAnalyze 5.0+ (`read_npx` / `read_NPX`)
Output: npx_long_raw.rds; import log with sample and assay counts
OlinkIDs, duplicate sample IDs, assay QC warnings, and UniProt mapping are validated via `check_npx`. The check log feeds downstream functions (OlinkAnalyze 5.0+).
Tools used: OlinkAnalyze 5.0+ (`check_npx`)
Output: check_log.rds; data_integrity_report.csv
Invalid assays, failed QC flags, and external controls are removed per agreed thresholds (OlinkAnalyze 5.0+).
Tools used: OlinkAnalyze 5.0+ (`clean_npx`)
Output: npx_cleaned.rds; cleaning_log.csv
Plate distribution and sample NPX boxplots are reviewed. Outlier samples flagged by IQR or median rules are documented before exclusion or retention [3].
Tools used: OlinkAnalyze 5.0+ (`olink_dist_plot`, `olink_qc_plot`)
Output: sample_qc_summary.csv; plate and sample QC plots (PDF/SVG)
LOD is calculated from negative controls or fixed Olink LOD values. High-missingness assays are filtered before statistics [3].
Tools used: OlinkAnalyze 5.0+ (`olink_lod`); OlinkAnalyzeVignettes LOD tutorial
Output: lod_summary.csv; missingness_profile.csv; assay_filter_log.csv
Bridge samples are selected with `olink_bridge_selector`. Normalization uses median-of-paired-differences bridging, or quantile smoothing for cross-product merges (Explore 3072 to HT). PCA before and after bridging is used to check that batch separation is reduced [3].
Tools used: OlinkAnalyze 5.0+ (`olink_bridge_selector`, `olink_normalization_bridge`); OlinkAnalyzeVignettes bridging tutorials
Output: npx_normalized.csv; bridging_adjustment_factors.csv; pre/post bridging PCA plots
PCA on normalized NPX values is used to separate condition from plate or batch when that is possible. UMAP is added when scoped [3].
Tools used: OlinkAnalyze 5.0+; custom R (`umap` when scoped)
Output: PCA/UMAP plots (PDF/SVG); unsupervised_qc_summary.csv
Per-protein models match the design: `olink_ttest` or `olink_wilcox` for two groups, `olink_anova` for multi-group, or `olink_lmer` with plate or subject random effects. Benjamini-Hochberg FDR controls multiplicity (OlinkAnalyze 5.0+; [8] for limma contrasts).
Tools used: OlinkAnalyze 5.0+ (`olink_ttest`, `olink_anova`, `olink_lmer`); limma 3.60+ when design fits matrix contrasts
Output: dep_results_<contrast>.csv (OlinkID, UniProt, Assay, Estimate, SE, DF, pvalue, adj.pvalue, N)
Significant proteins feed GSEA or ORA via `olink_pathway_enrichment` against MSigDB, Reactome, KEGG, or GO. Volcano plots, heatmaps, and enrichment dot plots are bundled with scripts, README, and a Methods draft (OlinkAnalyze 5.0+; [9]).
Tools used: OlinkAnalyze 5.0+ (`olink_volcano_plot`, `olink_pathway_enrichment`)
Output: pathway_enrichment.csv; figure bundle (PDF/SVG); README; Methods draft
Multiple biological replicates per condition, often three or more, help estimate per-protein variance on NPX [5]. For a two-group design with mean ΔNPX = 0.5 and pooled SD = 0.8 (Cohen's d ≈ 0.63), roughly 41 samples per group yields 80% power at α = 0.05 for a single test. Testing hundreds of proteins requires larger cohorts and FDR control. Multi-project designs also need bridge samples (8-64 depending on Olink product pairing; [3]). Pepkio reviews power and bridge plans at kickoff.
Yes, with documented caveats. Warning-flagged samples and high-missingness assays are flagged in the QC report before differential testing. Outlier samples in PCA are discussed with you. A re-run on the Olink platform is recommended when QC failure threatens the study question. Retained warning samples are noted in the parameter log.
Yes, for NPX files exported from Olink software without manual alteration, when panel metadata and export format are confirmed at kickoff. OlinkAnalyze 5.0+ reads CSV, Excel, Parquet, and ZIP archives from NPX Manager, NPX Map, and NPX Explore pipelines. QUANT data can be analyzed when log-transformed per Olink guidance.
A standard project (single NPX project, roughly 20-200 samples, one primary contrast, DE testing, and pathway enrichment) typically completes in 2-4 weeks from data receipt. Multi-batch bridging, cross-product normalization (Explore 3072 to HT), mixed-model designs, or cohorts that need extensive QC review may take 4-8 weeks. Exact timelines are confirmed at kickoff.
When batch or project is known and not fully confounded with condition, Pepkio applies Olink bridge normalization using overlapping bridge samples and documents adjustment factors per assay [3]. For within-project multi-plate designs, plate may enter as a random effect in `olink_lmer`. Generic post-hoc correction without bridge samples is not applied to cross-project NPX comparisons.
Yes. You retain full ownership of all code, scripts, and results delivered under the project agreement. Pepkio provides commented R scripts with `renv` lock files or `sessionInfo()` exports. NPX matrices use `.csv`, `.tsv`, and `.rds` formats. R Markdown delivery is available on request.
Yes. Checkpoint reviews occur after data integrity QC, after bridging normalization, and before final delivery. You can review contrast definitions, bridge-sample lists, LOD filtering thresholds, and FDR cutoffs within agreed scope. A dedicated scientific contact leads the project and documents decisions in the QC report and Methods draft.
Clarification of normalization, bridging, LOD handling, statistical models, and minor figure or table revisions within agreed scope (typically ≤20% of deliverables). It does not include open-ended reanalysis or new biological contrasts. Substantial new work is scoped as separate milestones.
No. Pepkio operates as a fee-for-service provider unless co-authorship is discussed and agreed in advance. You retain ownership of results and code delivered under the project agreement.
Not for valid joint inference. NPX is a relative log₂-scaled unit normalized within each project, so separate projects need bridge normalization using overlapping biological samples [3]. Pepkio analyzes single-project datasets without bridging when that is appropriate, or sets bridge-sample requirements before merging multi-batch data.
Per-assay LOD is calculated using `olink_lod` [3]. Assays where a large fraction of samples fall below LOD are typically excluded from DE testing. For retained assays with sporadic below-LOD values, Pepkio documents the handling rule (complete-case analysis, censoring, or pre-specified half-LOD imputation) in the parameter log before modeling.
OlinkAnalyze is the default because the functions are panel-aware, apply BH-FDR across OlinkIDs, and support mixed models with plate random effects (`olink_lmer`; OlinkAnalyze 5.0+). limma 3.60+ is used when the design fits a standard matrix contrast and the client requests limma-specific outputs [8]. The choice is documented at kickoff.
Tell us:
We'll tell you:
Contact us to start with a free consultation. Need everyday bench calculators? Try our free lab tools.
