Download data | Seasonal heatmap | Monthly trend lines with min/max ribbon | Diurnal range | Regional comparison

ERA5 data | Bounding box | GeoJSON region | Point location | IMD data | Rainfall | Temperature | Find variables | Cache

Bulk RNA-seq | Human, gene symbols | Mouse, Ensembl gene IDs | Mouse, transcript IDs | Single-cell RNA-seq | Human | Mouse | Species without XIST | Rat: males only | Zebrafish: no panel | Summary

Old Ensembl IDs from a 2014 single-cell experiment | Correct Excel-damaged names in a real deposited matrix | Historical versus newer symbols

Installation | Search the archives | Query studies | Query samples (cohorts) | Everything pipes | Retrieve study metadata | Harmonized sample attributes | Read counts matrices | List counts files | Load a matrix | Convert to Seurat | Convert old gene IDs and repair Excel errors | Download data files | Choose a backend | Next steps

Detecting species | Determining the annotation release | Handling GENCODE and Ensembl | Caution around new releases

At a glance | Bhuvan: simple India annual data | NASA Black Marble: annual, monthly, and daily | Comparison

State-level workflow (bundled boundaries) | District-level workflow | LGD boundaries | Historical census boundaries | VIIRS path

All states, all years | Single state time series | Compare states | Nighttime India from space, 2012 to 2024 | Filter by year range

Get a NASA Earthdata token | Quick workflow | Use your own shape/boundary file

Overview | Resistance Profile Estimation | Option 1: Convex Optimisation (Pathway 1) | 1.1 Aggregate Input: Validate Marginals | 1.2 Profile Enumeration | 1.3 Constraint Matrix | 1.4 Estimate Profile Probabilities | 1.5 Facility Line-List Pathway | 1.6 Check Constraint Satisfaction | 1.7 Bootstrap Uncertainty Intervals | Option 2: Bayesian Multivariate Probit (Pathway 2) | 2.1 Prepare Event-Level Class Data | 2.2 Fit the Model | 2.3 Convert Posterior Draws to Resistance-Profile Probabilities | 2.4 Aggregate for DALY | 2.5 Validate Calibration | 2.6 Predictive Checks | 2.7 Unified Dispatcher | 2.8 Post-Fit Checklist: What to Run, and Why | Pipeline at a Glance | Session Info

Install | Match against a reference list | Match on meaning | Choose a model without labels | Cluster without a reference list

What is anumaan? | Pipeline 1 — Preprocessing | Pipeline 2 — Exploratory Data Analysis | Pipeline 3 — DALY Burden Estimation | Bayesian multivariate probit backend selection | Installation | Optional dependencies | Data Format | Package Reference

Overview | Connecting from Pipeline 1 | A Small Synthetic Dataset | Theme | Organism and Susceptibility Overview | Top organisms | Susceptibility pattern (stacked R/S bars) | Resistance heatmap | Resistance by specimen type | Resistance by age bin and by organism | Outcomes | Overall distribution | Outcome by organism, split by resistance status | Death vs. discharged | Outcome by age bin and by year | Case-Mix and Facility Patterns | Patients per hospital | Monomicrobial vs. polymicrobial, by facility | HAI vs. CAI, by facility | Location (ICU vs. Ward), by facility | Infection type by location | Syndrome distribution | Length of Stay and Age Distributions | LOS ridge plot | Age ridge plot | LOS by age bin | Pipeline at a Glance | Summary | Session Info

Overview | A Small Synthetic Raw Dataset | Schema Checks and Column Mapping | Inspect what preprocessing is possible | Build a rename map explicitly | One-step convenience wrapper | Assert the minimum standard names | Dates and Table Validation | Parse a single vector of mixed date encodings | Validate and coerce the working table | Validate chronology | Standardize Core Clinical Fields | Organisms | Specimen, sex, outcome, and infection type | Antibiotics and AST values | Demographic and Clinical Derivations | Fill age and assign age bins | Derive length of stay | Derive HAI/CAI and source flags | Assign facility type | Event Creation and AST Reshaping | Create event IDs from long-format isolates | Deduplicate event-level rows | Classify readmissions from admission dates | Standardize non-conforming readmission labels | Pivot wide AST input to long format | Deduplicate AST records | MDR/XDR Classification | Collapse to class level | Classify MDR/XDR | Contaminants and Polymicrobial Episodes | Flag likely contaminants | Exclude fungal isolates when needed | Flag and weight polymicrobial episodes | Attrition and Analysis Readiness | Track attrition across preprocessing stages | Final readiness checks | Summary