CattleCell-GTEx / Help

Database
user guide.

How to search the CattleCell-GTEx database, select datasets, filter and sort result tables, view plots, and download data. This guide explains website operations, not how to run the underlying analyses.

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Choose a database entry point

Use the homepage search for a gene or variant, or select a dataset from the navigation menu to browse its records. Tissue and cell-type filters are available only in tables with the corresponding input boxes; the homepage search is not a tissue or trait search.

Select a datasetFilter its recordsView or export results

A few controls you will use throughout

  • Filter: on a dataset page, type into an input beneath a column heading and press Enter. Multiple column filters are applied together. Clear an input and press Enter to remove that filter. Text filters generally match the beginning of a value, rather than any occurrence within it; check the returned identifiers even when entering a full ID. Numeric inputs are not range expressions: do not enter conditions such as <0.05.
  • Read a field: hover over the exclamation-mark icon beside a column name for its definition. A displayed column is not necessarily filterable or sortable.
  • Sort: select a sortable heading to change the order. Only supported fields can be sorted; the request is applied on the server.
  • Navigate: use the table pagination controls and horizontal scrollbar to see additional rows and columns.
  • Export: “Export current page” saves the displayed page, not every matching record. Use Download for available bulk files.

Browse expression and fraction data

Molecular phenotypes

Gene expression

Find a gene and inspect its expression across tissues or tissue–cell-type combinations. The table includes genomic coordinates and separate chart controls for the two expression views.

  1. Open Molecular phenotypes → Gene expression. Filter by Gene Id, Start, End or Chromosome, then press Enter. This table has no gene-symbol, tissue or cell-type filter; use the homepage search first if you only know a gene symbol.
  2. Select the chart icon under Tissue Expression or Tissue_Celltype Expression in the required gene's row.
  3. Both box-plot views display log2(TPM + 1) for non-zero TPM records and order groups by ascending median expression. They show distributions, not a single average expression value. Hover over the plot to inspect values; close the dialog to return to the table.
Gene expression table with gene coordinates and expression chart controls Enlarge screenshot
Locate the gene first, then use the chart controls to choose the expression context.
Tissue expression box plot for an example gene Enlarge screenshot
The expression plot displays the available non-zero TPM observations. Read the axis and group labels before comparing distributions.
Open gene expression ↗

Cell type fraction

Open Molecular phenotypes → Cell type fraction. Filter by IID (sample), Tissue, Cell type or a numeric Fraction value, then press Enter. Select the icon in Plot to open a stacked bar chart for that row's tissue, with separate cell-type series. Zero-fraction records are excluded from both the table and plot queries.

Cell type fraction table with tissue, cell type and chart controls Enlarge screenshot
Use tissue and cell-type context together when reading a fraction.
Open cell type fraction ↗

Browse eQTL datasets

QTL / eQTL

Select the analysis context before filtering. The four eQTL entries are separate datasets, not interchangeable views of a single result.

The menu offers Bulk_eQTL, Cellstate_ieQTL, Celltype_ieQTL and Celltype_seQTL. Select one to open its table.

  1. Choose a dataset under QTL → eQTL.
  2. Enter a gene ID in pheno_id, a tissue in tissue_name, a variant ID in variant_id_x or a dbSNP ID in rsid, then press Enter. Try ENSBTAG00000015728 in Bulk_eQTL. The celltype_name column is displayed but has no filter input.
  3. The table initially sorts pval_g1_x in ascending order. Select that heading to reverse the order, use the page controls to browse more matches, or export the current page. The other eQTL columns do not have sorting controls.
Bulk eQTL results filtered by ENSBTAG00000015728 Enlarge screenshot
Real Bulk_eQTL matches for ENSBTAG00000015728. Scroll horizontally in the live table to reach the association statistics.

Viewing result columns

Scroll horizontally to reach additional columns, including REF, ALT, beta_g1_x and pval_g1_x. Hover over a column's information icon for its definition, or select the pval_g1_x heading to switch the sort order.

Browse fine-mapping records

Fine mapping

Browse the stored fine-mapping results for Bulk_eQTL or Celltype_seQTL. Selecting a dataset displays existing records; it does not run a new fine-mapping analysis.

  1. Select QTL → Fine mapping and choose a dataset.
  2. Filter using the SNP, rsid, gene or tissue_name input, then press Enter.
  3. Results initially sort by PIP in descending order. Select the PIP heading to reverse it. cs, ct and annotation columns are available for reading, not filtering.
Fine-mapping table with candidate SNPs, genes, credible sets and PIP Enlarge screenshot
The live table also includes functional annotation fields; scroll to inspect them alongside the statistical evidence.

Browse independent-signal data

Independent signals

Browse the bulk or cell-type independent-signal tables. Each record includes gene, tissue and model fields.

  1. Choose QTL → Independent, then Bulk_eQTL or Celltype_eQTL.
  2. Filter by pheno_id, tissue, map_model or variant_id and press Enter.
  3. Scroll to view beta_g1, beta_se_g1 and pval_g1. The af, beta_g1, beta_se_g1 and pval_g1 headings support sorting.
Independent bulk eQTL signals table Enlarge screenshot
Independent-signal records retain their analysis model and tissue context.

Browse model and result tables

TWAS

TWAS models

Open TWAS → TWAS models. Enter an Ensembl gene ID in gene or a gene symbol in gene_name, then press Enter. This table displays stored prediction-model metrics; it has no tissue or cell-type columns and does not train a new model.

Sortable fields are test_R2_avg, test_R2_sd, cv_R2_sd, rho_avg, rho_se, rho_avg_squared, zscore_pval, cv_rho_avg_squared, cv_zscore_pval and cv_pval_est. Hover over a field's exclamation-mark icon for its definition.

TWAS prediction models with performance metrics Enlarge screenshot
Filter by gene, scroll horizontally to view model-performance columns, and select a sortable heading to change the order.
Open TWAS models ↗

TWAS results

Open TWAS → TWAS results. Filter by gene or gene_name and press Enter. Scroll horizontally to read the columns displayed as tissue_celltype (underlying field tissue_ct) and trait_name; these columns have no filter inputs. You can sort pvalue, zscore, effect_size, pred_perf_r2, pred_perf_pval and best_gwas_p.

TWAS results with association statistics and prediction performance Enlarge screenshot
Use the gene or gene_name filter to find records, then scroll horizontally to view tissue_celltype and trait_name.
Open TWAS results ↗
Trait names & descriptions 44 traits in TWAS results

Use this reference to interpret the abbreviations in the trait_name column.

44 of 44 traits

TWAS trait abbreviations, full names and brief descriptions
AbbreviationFull trait nameDescription
Dtr_Calv_EaseDaughter calving easeEase of calving experienced by daughters during parturition.
Dtr_Still_BirthDaughter stillbirthIncidence of stillbirths in calves delivered by daughters.
Sire_Calv_EaseSire calving easeGenetic effect of sires on calving difficulty in offspring.
Sire_Still_BirthSire stillbirthGenetic effect of sires on stillbirth incidence in offspring.
gestlengGestation lengthDuration of pregnancy from conception to calving.
CALCHypocalcemiaSusceptibility to low blood calcium levels (milk fever).
DSABDisplaced AbomasumSusceptibility to displacement of the abomasum in dairy cattle.
KETOKetosisSusceptibility to metabolic ketosis during lactation.
MASTMastitisSusceptibility to udder inflammation and infection.
METRMetritisSusceptibility to uterine infection after calving.
RETPRetained PlacentaFailure to expel placenta after calving.
Calf_LivabilityCalving livabilitySurvival rate of calves at or shortly after birth.
Cow_Conc_RateCow conception rateFertility trait measuring conception success in cows.
Dtr_Preg_RateDaughter pregnancy rateReproductive efficiency based on daughter pregnancy performance.
Early_calvingEarly calvingTendency for heifers or cows to calve earlier.
Heifer_Conc_RateHeifer conception rateFertility trait measuring conception success in heifers.
LivabilityLivabilityOverall survival and longevity of cows in the herd.
Net_MeritNet MeritComposite economic index summarizing overall profitability.
Prod_LifeProductive lifeLength of productive lifespan in dairy production.
SCSSomatic cell scoreIndicator of udder health and mastitis resistance.
Body_depthBody depthDepth of the body cavity and rib structure.
Dairy_formDairy formOverall dairy character and angularity of the cow.
Feet_and_legsFeet and legsStructural quality and soundness of feet and legs.
Final_scoreFinal scoreOverall conformation evaluation score.
Foot_angleFoot angleAngle and structure of the hoof and pastern.
Fore_udder_attFore udder attachmentStrength and quality of fore udder attachment.
Front_teat_plaFront teat placementPosition of front teats relative to udder structure.
Rear_legs(rear)Rear legs (rear view)Rear leg structure evaluated from the back view.
Rear_legs(side)Rear legs (side view)Rear leg structure evaluated from the side view.
Rear_teat_plaRear teat placementPosition of rear teats relative to udder structure.
Rear_ud_heightRear udder heightHeight of rear udder attachment.
Rear_ud_widthRear udder weightWidth of rear udder attachment.
Rump_angleRump angleAngle and slope of the rump structure.
Rump_widthRump widthWidth of the rump and pelvic region.
StatureStatureOverall body height of the animal.
StrengthStrengthOverall body strength and robustness.
Teat_lengthTeat lengthLength of teats used for milking.
Udder_cleftUdder cleftStrength of the median suspensory ligament of the udder.
Udder_depthUdder depthDepth of the udder relative to the hock.
FatFat yieldTotal milk fat production.
Fat_PercentFat percentagePercentage of fat content in milk.
MilkMilk yieldTotal volume of milk production.
Pro_PercentProtein percentagePercentage of protein content in milk.
ProteinProtein yieldTotal milk protein production.

Browse colocalization records

Colocalization

The navigation provides separate gene-level and QTL-level result tables. Choose the corresponding entry before filtering records.

Gene-level results

Under Colocalization, choose Bulk_eGene, Cellstate_ieGene, Celltype_ieGene or Celltype_seGene. Filter by gene_id, tissue or celltype and press Enter. The traits column is display-only. Only the displayed res.summary heading (underlying field res_summary) supports sorting; hover over its information icon for the field definition.

Gene-level colocalization table including traits and posterior probability Enlarge screenshot
View values in the res.summary column and select its heading to change the sort order.

QTL-level results

Choose Bulk_eQTL, Celltype_eQTL or Celltype_ieQTL to inspect the corresponding QTL records. Filter by pheno_id or variant_id and press Enter; tissue_name and trait_name are display-only. Scroll horizontally to view additional fields. The af, beta_g1, beta_se_g1 and pval_g1 headings support sorting.

QTL-level colocalization table with variant association fields Enlarge screenshot
QTL-level entries provide the variant-level context complementary to the gene-level summary.

Browse selection-signal data

Selection Signal

The current entry opens the fst10_cseQTL dataset, with identifier and annotation columns.

  1. Filter by pheno_id, tissue_name, ct_name or the column labelled varaint_id, then press Enter.
  2. You can also filter by ATAC_status, Chromatin_state, Enrichment or SNP_annotation.
  3. Hover over an information icon for the column definition. No headings in this table provide sorting controls.
Selection Signal table with QTL identifiers and functional annotations Enlarge screenshot
Use the tissue, cell-type or variant filters to locate records, then scroll horizontally as needed to view the annotation columns.
Open Selection Signal ↗

Work with the source files

Download

The Download page groups dataset file links. Some files are listed now; the page notes that the complete dataset will be made available upon publication.

  1. Locate the relevant category and read the dataset description.
  2. Expand a grouped category where an expansion control is provided.
  3. Select the download icon for the required file. Links may open an external file host; large transfers depend on that host and your connection.
Download page showing dataset categories and download links Enlarge screenshot
Choose the dataset by its description and file name, not just by the nearest download icon.
Open downloads ↗

When you need a hand

FAQ & support

Why does my search return no records?

Check the identifier format and spelling, select the intended dataset, and clear restrictive filters. A successfully loaded table with zero matches is different from a request that fails or stays on a loading indicator. If loading fails, record the module, query and filters, then contact support.

Why are results different between modules?

Each module queries a different dataset. Available columns and matching record counts may differ even when you use the same identifier.

Why is my exported CSV smaller than the match count?

“Export current page” exports only the currently displayed page. The total count describes all matching rows. Visit Download for available bulk files.

How do I see columns or plots that are off screen?

Scroll horizontally within wide tables. On gene-expression and cell-fraction pages, select a chart icon to open the plot. On this Help page, select a screenshot to enlarge it; press Escape or use Close to return.

Why are some result groups hidden?

On the combined search page, gene searches show molecular expression, expression plots, JBrowse, QTL, fine mapping, independent signals, colocalization and TWAS. Variant searches show only QTL, fine mapping and independent signals; the other groups are hidden by design. See Home & search for examples.

How should I cite the resource?

Use the citation shown on the homepage and check the linked publication for its current bibliographic details. Record the dataset context and access date for your analysis.

Still need help?

Include the module, query identifier, selected filters and a description of what happened. Do not send passwords or private data.

Technical support ↗Scientific enquiries ↗

Screenshots are cropped from real interface captures at a 2560 × 1440 viewport. Enlarge an image to view it fitted to the window. They are examples, not a guarantee of current row counts or data availability.