Plugins

1 plugin

Brand Consistency Review

Check brand expression, flag divergences, and suggest corrections for a single screen.

10 skills · plugin

Results for “express”

33 skills

Perform differential gene expression analysis for bulk RNA-seq data using PyDESeq2, supporting formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.

30.2k · bundle

Access NCBI GEO (Gene Expression Omnibus) for gene expression and functional genomics data — search and download microarray and RNA-seq datasets by GSE, GSM, GPL, or GDS accession and retrieve SOFT, MINiML, and series matrix files. Use when locating public expression datasets, fetching processed expression matrices, downloading a study's supplementary files, or sourcing per-study transcriptomics data for differential-expression analysis. For raw FASTQ sequencing reads by SRA/ENA run accession use alterlab-ena; for reference tissue-expression baselines (median TPM across human tissues) use alterlab-gtex; for cancer cohort somatic mutations and copy-number use alterlab-cbioportal. Part of the AlterLab Academic Skills suite.

Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.

Backend Patterns

Provides backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Performs differential expression analysis on label-free quantitative (LFQ) proteomics data from MaxQuant and DIA-NN outputs, including preprocessing, imputation, statistical testing, and visualization.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

30.2k · bundle

More results

schattenspiegel

Build, verify, and debug interactive Python visualizations with Plotly, including Plotly Express, graph_objects, subplots, facets, hover/customdata, axes, legends, FigureWidget events, and HTML/image export.

Tao Generate Image Grounding

Generates phrase-grounded bounding box annotations from image-caption pairs using a VLM, producing cleaned captions, referring expressions, and pixel-space bounding boxes.

Creates interactive Plotly visualizations in Python, covering Express and Graph Objects for scatter, line, bar, heatmap, 3D, and geographic charts, plus subplots, styling, and HTML export.

Create interactive, publication-quality visualizations with 40+ chart types, hover, zoom, pan, and web embedding. Choose between Plotly Express and Graph Objects for dashboards, exploratory analysis, and presentations.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

metinduraktr-44

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Creates interactive, publication-quality charts with hover, zoom, and pan, plus static exports and Dash integration.

nimoqup046-collab

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.

Biblioteca DataFrame rápida (Apache Arrow). Selecione, filtre, group_by, joins, avaliação preguiçosa, I/O CSV/Parquet, expression API, para fluxos de trabalho de análise de dados de alto desempenho.

Queries 20+ bioinformatics databases from the command line or Python for gene info, sequences, BLAST/BLAT, protein structures, viral data, and expression metrics.

Creates interactive, publication-quality charts with 40+ types, hover tooltips, zoom, and web-embeddable exports for dashboards and exploratory analysis.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.

Run standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.

30.2k · bundle

Infer gene regulatory networks from gene expression data using scalable algorithms (GRNBoost2, GENIE3) with support for distributed computation.

30.2k · bundle

Extracting Windows Event Logs Artifacts

Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

24.6k · bundle

Process in-memory tabular data with a fast, expression-based DataFrame library that supports lazy evaluation, parallel execution, and Apache Arrow semantics.

Export Premiere

Exports a timeline.json as a Premiere Pro editor packet, including FCP7 XML, captions, and media, with verification steps.

Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.

30.2k · bundle

Provides deep generative models for single-cell omics analysis, including probabilistic batch correction, transfer learning, differential expression, and multi-modal integration.

30.2k · bundle

lucaspmarie-a11y

Process in-memory datasets with Polars' expression API, lazy evaluation, and parallel execution, including pandas migration patterns and I/O for CSV, Parquet, and JSON.

nimoqup046-collab

Creates interactive, publication-quality visualizations in Python with 40+ chart types, including scatter, bar, heatmap, 3D, and financial charts, plus subplots, styling, and export to HTML or static images.

Cellxgene Census

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data, enabling efficient access to cell metadata, gene expression slices, summary counts, and embeddings without downloading whole datasets.

30.2k · bundle

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

mariadb-corporation

Mariadb Create Index

Explains MariaDB-specific CREATE INDEX and DROP INDEX syntax, including mapping to ALTER TABLE, prefix lengths for TEXT/BLOB, lack of expression indexes, real descending indexes, IGNORED indexes, and index kinds. Use when writing or reviewing index statements for MariaDB.

Wydruki i raporty w Soneta (enova365, Triva) — pliki .repx (DevExpress XtraReports, serializowany XML). Sięgaj przy KAŻDYM zadaniu z wydrukiem/raportem: faktura, dokument, deklaracja, lista, zestawienie; utworzenie, przeróbka lub poprawa .repx (też z załącznika); pytanie „jak w wydruku zrobić X”. Typowe X: podpięcie danych (lista, dokument z pozycjami, master-detail, podraport), podział stron, kolumna Lp, tabele, grupowanie i sumy, formatowanie warunkowe, kwoty, nakładanie wartości na skan formularza, nagłówek/stopka/podpisy, arkusz stylów (.repss), rejestracja wydruku. Wyzwalają też pojęcia: XtraReportsLayoutSerializer, StyleSheetSerializer, pasma (DetailBand/DetailReportBand/GroupHeaderBand/SubBand), kontrolki (XRLabel/XRTable/AmountLabel), BusinessDataSource/DataKind, ReportContext, ExpressionBindings/Summary/CalculatedFields/FilterString, [assembly: DxReport], ReportSnippet/[DxBind]. Wystarczy „wydruk”, „raport” lub „.repx” w kontekście Soneta. NIE dla: business.xml, form.xml, SQL, Excel, Word .dotx.

Alterlab Cbioportal

Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data. Use when asked how often a gene is mutated/amplified/deleted in a tumor type, to profile oncogenes or tumor suppressors across cancers (pan-cancer alteration frequency), to pull patient-level mutations joined to OS/clinical outcomes, or to validate a cancer target from cohort genomics. For germline variant pathogenicity use alterlab-clinvar; for mutational-signature (SBS) decomposition use alterlab-cosmic; for CRISPR/RNAi gene-dependency use alterlab-depmap; for aggregated target-disease evidence use alterlab-opentargets. Part of the AlterLab Academic Skills suite.