aviputri

arcgis-python-api

Documentation and samples for ArcGIS API for Python

arcpy-water-extraction

args-kwargs-example

Land-Cover-Classification

Scripts used for land cover classification in Python. Currently using Random Forest method.

Land-Cover-Classification-with-Feature-Selection

The training data will be reduced to some random sampling, and the feature importance is calculated

Land-Cover-Classification-with-SF

using random forest method to classify LS7 and LS8 imagery together with their spectral features

mean-shift-clustering

A python script to segment images using the mean shift discontinuity preserving filter and clustering.

Ocean-Wave-Spectra

A tool to generate a spectrum of a set of sea water level (SWL) data, and then to create a synthetic SWL and classify the synthetic waves parameters.

Random-Forest-for-Land-Cover-Classification

Using Landsat 7 SLC Off imagery. All functions in functions.py

Unit-Hydrograph

To create a synthetic unit hydrograph (UH) using Wackermann method.

aviputri/arcpy-water-extraction

aviputri/arcgis-python-api

Documentation and samples for ArcGIS API for Python

aviputri/Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

aviputri/basemap-styles

CARTO basemap public styles

aviputri/convert-raster-to-polygon

aviputri/custom_colormap

Code for generating custom Matplotlib colormaps from RGB or HEX values

aviputri/density-scatter-plot-py

aviputri/earthengine-api

Python and JavaScript bindings for calling the Earth Engine API.

aviputri/flood-mapping-tsx

aviputri/floodmap-accuracy

aviputri/gee-mapping-source

source code for google earth engine mapping routines

aviputri/GEE-tutorial

aviputri/gee_otsu_js

aviputri/GEE_Sentinel2_Bathymetry_Paper

This is the Google Earth Engine code for generating bathymetry in "Automated global coastal water bathymetry mapping using Google Earth Engine" paper.

aviputri/geemap

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets

aviputri/geetools-code-editor

A set of tools to use in Google Earth Engine Code Editor (JavaScript)

aviputri/GrovePi

GrovePi is an open source platform for connecting Grove Sensors to the Raspberry Pi.

aviputri/img-segmentation-tutorial

based on https://www.analyticsvidhya.com/blog/2019/04/introduction-image-segmentation-techniques-python/

aviputri/import-plt

aviputri/LCC-TSX

aviputri/loop-gdal-ogr

aviputri/medium_posts

Code linked to blog posts on data science and machine learning topics.

aviputri/OpenCV2-Python-Tutorials

This repo contains tutorials on OpenCV-Python library using new cv2 interface

aviputri/persona5_calculator

A tool to help calculate fusions in Persona 5.

aviputri/PyGObject-Tutorial

Tutorial for using GTK+ 3 in Python

aviputri/qgis-earthengine-examples

A collection of 300+ Python examples for using Google Earth Engine in QGIS

aviputri/satellite-image-deep-learning

Resources for deep learning with satellite & aerial imagery

aviputri/sdb_gui

Python based GUI for Satellite Derived Bathymetry processing

aviputri/segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

aviputri/Source-Code-from-thenewboston-Tutorials

Here is the source code from all of my tutorials.