Sowpati lab

ATaRVa - Analysis of Tandem Repeat Variation from long read sequencing data

Long-read sequencing propelled comprehensive analysis of tandem repeats (TRs) in genomes. Current long-read TR genotypers are either inaccurate, platform-specific, or computationally inefficient. Here we present ATaRVa, a sequencing technology-agnostic genotyper that outperforms existing tools while running an order of magnitude faster. ATaRVa also supports short-read data, multi-threading, consensus sequence derivation, and motif decomposition, making it an invaluable tool for population scale TR analyses.

DELTA - Visualizing processed RNAseq data

DELTA is a web application written with the intent to make RNAseq data visualization accessible to biologists who may not necessarily have the coding knowledge to visualize RNAseq datasets on platforms like R or python. Through delta we hope to make the tools for hypothesis testing and quick visualization available to researchers of any technical skill level.

DiviSSR - Identification of tandem repeats based on simple arithmetic

DiviSSR puts forth a novel idea of pattern identification of DNA sequences. We uncover a fascinating characteristic of repeat sequences when we disguise them as numbers. Repeat numbers of similar structure are all divisible by a specific number or leave a distinct remainder when divided by the number. This magical number we call DiviSSR (as it divides all simple sequential repeats). Computers are built on bits which is a number system of two digits. Hence, we use 2-bit representation to convert DNA sequences to numbers and process them to identify repeats. DiviSSR takes a mere 30 seconds to identify repeats in the human genome working on a common everyday-use laptop.

MSDB - A comprehensive database of microsatellites

Microsatellite DataBase (MSDB) is the largest collection of short tandem repeats (STRs) data from all sequenced genomes. The database currently hosts STR data for >40,000 genomes which were mined from NCBI and UCSC Genome repositories. MSDB is equipped with a strong visualization platform which offers a comprehensive characterization of STRs in a genome based on parameters such as motif characteristics, length and genomic context. Championing Dobzhansky’s statement “Nothing in biology makes sense except in the light of evolution”, MSDB has equipped an interactive special platform for user-defined analysis to compare the STR profiles across different organisms for exploratory evolutionary analysis. PERF - Perfect, Exhaustive Repeat Finder
PERF, released in 2019, was the fastest tandem repeat identification tool compared to its contemporaries. The tool is based on an unconventional method for identifying STRs which relies on either / both ? direct string comparison or heuristic modeling of the repetitive nature of DNA sequence. We use hashing to store all known repeat sequences with the desired parameters and assert genomic subsequences as repeats based on their membership in the hash set. PERF brought down the identification of STRs in the human genome to a time as low as 2 minutes. We beat this time with our own tool DiviSSR.

NEMO - Nanopore Epigenetic Modification Output

DNA methylation plays a key role in epigenetic regulation across lifeforms. Nanopore sequencing enables direct detection of base modifications. While multiple tools are currently available for studying 5-methylcytosine (5mC), there is a paucity of models that can detect 6-methyladenine (6mA) from raw nanopore data. Leveraging the motif-driven nature of bacterial methylation systems, we generated 6mA identification models that vastly surpass the accuracy of the current best model. Our work enables the study of 6mA at a single-base resolution in new as well as existing nanopore datasets.

PERF - Perfect, Exhaustive Repeat Finder

PERF is a Python package developed for fast and accurate identification of microsatellites (SSRs) from DNA sequences. The existing tools for SSR identification have one or more caveats in terms of speed, comprehensiveness, accuracy, ease-of-use, flexibility and memory usage. PERF was designed to address all these problems.
PERF is a recursive acronym that stands for "PERF is an Exhaustive Repeat Finder". It is compatible with both Python 2 (tested on Python 2.7) and 3 (tested on Python 3.5). Its key features are:

Fast run time, despite being a single-threaded application. As an example, identification of all SSRs from the entire human genome takes less than 7 minutes. The speed can be further improved ~3 to 4 fold using PyPy (human genome finishes in less than 2 minutes using PyPy v5.8.0)
Linear time and space complexity (O(n))
Identifies perfect SSRs
100% accurate and comprehensive - Does not miss any repeats or does not pick any incorrect ones
Easy to use - The only required argument is the input DNA sequence in FASTA format
Flexible - Most of the parameters are customizable by the user at runtime
Repeat cutoffs can be specified either in terms of the total repeat length or in terms of number of repeating units
TSV output and HTML report. The default output is an easily parseable and exportable tab-separated format. Optionally, PERF also generates an interactive HTML report that depicts trends in repeat data as concise charts and tables

Ribbit - Repeat identification based on bit operations

DNA tandem repeats (TRs) are crucial for genomic functions like protein binding, chromatin modulation, splicing, and gene regulation. Abnormal length variations in TRs, especially expansions, are associated with over 60 neurodegenerative diseases. The function and stability of a TR locus is dependent on its sequencing composition and purity. Recent studies report the disease-causing propensity of non-canonical motif expansions in TR loci, and highlight the intricate polymorphism dynamics in complex loci encompassing adjacent, overlapping, and nested TRs. These reports emphasize the need for precise definition and motif decomposition of TR loci. To address this, we present Ribbit, a tool that accurately and efficiently identifies and annotates TR loci in a genome. Ribbit uses 2-bit representation of DNA sequences for rapid identification of TRs of 2–100 bp motif size and resolves complex TR structures. Ribbit efficiently handles imperfections such as indels and substitutions, providing insights into nested and compound TR relationships through detailed motif decomposition. Comparative analyses using simulated data show Ribbit outperforms existing tools like Dot2dot and TRF in terms of runtime and accuracy. Ribbit reports TR loci in the human genome with lower redundancy than TRF and provides resolved TR regions comparable to variation clusters reported in recent catalogues. Therefore, Ribbit can be leveraged to understand the evolution and biology of complex TR regions in large genomes.

GEAR-19 Genome Evolution Analysis Resource

C-State - 'C' the Chromatin State

Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. Its potential for identifying user-defined epigenetic trends in context of gene expression profiles is demonstrated at the Het C-State page and in the case studies in the user manual.

GET - Genomes Exploration Tool

The NCBI Genome database is a collection of information on all the genome sequencing projects done and are in progress till date. NCBI provides a very basic browsing interface, which represents the whole data in a tabular format and has limited options for a user to explore through the genomes and find the information they need. To provide a user-friendly and interactive tool to explore this data, we developed Genomes Exploration Tool (GET) using a JavaScript plotting library called d3.js. GET uses data provided by NCBI and converts it into clear, interactive and visually appealing plots, which can be navigated and interacted with as the user desires. Using attributes such as Genome size, GC content, Number of genes and proteins etc. for more than 18000 genomes, users can explore the genomes using bar plots, scatter plots, box-and-whisker plots and histograms.