krishan57gupta
I am a research scholar working with the advisor Dr Debarka Sengupta, Computer Science and Center for Computational Biology Department, IIIT Delhi.
Delhi, India
Pinned Repositories
BPSC
Beta-Poisson model for single-cell RNA-seq data analyses
DOSeq
DOSeq - Modeling expression drop-out for analysis of scRNA-Seq data. DOSeq takes read count matrix and factor for drop-out ratio as input and return the read count matrix with dropout. Here input parameter factor indicates drop-out ratio in expression matrix.
HDS
iCTC
The goal of iCTC is to detect whether peripheral blood cells have CTCs (circulating tumor cell) or not.
my_web
ORsurv
survival of patients using ors on TCGA data
ROSeq
ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. Takes in the complete filtered and normalized read count matrix, the location of the two sub-populations and the number of cores to be used.
scanpy
Single-Cell Analysis in Python. Scales to >1M cells.
Stardust_package
cell-gene coembedding and analysis pipeline for single cell transcriptomics data
The-cellular-basis-of-the-loss-of-smell-in-2019-nCoV-infected-individuals
A prominent clinical symptom of 2019-nCoV infection is hyposmia/anosmia (decrease or loss of sense of smell), along with general symptoms such as fatigue, shortness of breath, fever, and cough. The identity of the cell lineages that underpin infection associated with loss of olfaction could be critical for the diagnostics/clinical management of 2019-nCoV infected individuals. Angiotensin I Converting Enzyme 2 (ACE2), and Transmembrane protease serine 2 (TMPRSS2) are emerging as associated host receptors vital for viral entry. Accordingly, the ongoing medical examinations and the autopsy reports of the deceased individuals strongly corroborate with the organ/cell-type-specific expression of ACE2, TMPRSS2, and other putative viral entry-associated genes. To determine the cellular basis of anosmia upon 2019-nCoV infection, we employed a targeted bioinformatic analysis of single-cell expression profiles of human olfactory epithelium cell-types. Our results underscored selective expression of these viral entry-associated genes in a subset of sustentacular cells, Bowman’s gland cells, and stem cells of the olfactory epithelium. Co-expression analysis of ACE2 and TMPRSS2 and protein-protein interaction among the host and viral proteins elected regulatory cytoskeleton protein-enriched sustentacular cells as the most vulnerable cell-type of the olfactory epithelium. Furthermore, expression, structural and docking analyses of these viral-entry moieties revealed the potential risk of olfactory dysfunction in four additional mammalian species, revealing an evolutionarily conserved susceptibility. In summary, our findings suggest the molecular and cellular rationale of loss of smell in 2019-nCoV infected patients.
krishan57gupta's Repositories
krishan57gupta/The-cellular-basis-of-the-loss-of-smell-in-2019-nCoV-infected-individuals
A prominent clinical symptom of 2019-nCoV infection is hyposmia/anosmia (decrease or loss of sense of smell), along with general symptoms such as fatigue, shortness of breath, fever, and cough. The identity of the cell lineages that underpin infection associated with loss of olfaction could be critical for the diagnostics/clinical management of 2019-nCoV infected individuals. Angiotensin I Converting Enzyme 2 (ACE2), and Transmembrane protease serine 2 (TMPRSS2) are emerging as associated host receptors vital for viral entry. Accordingly, the ongoing medical examinations and the autopsy reports of the deceased individuals strongly corroborate with the organ/cell-type-specific expression of ACE2, TMPRSS2, and other putative viral entry-associated genes. To determine the cellular basis of anosmia upon 2019-nCoV infection, we employed a targeted bioinformatic analysis of single-cell expression profiles of human olfactory epithelium cell-types. Our results underscored selective expression of these viral entry-associated genes in a subset of sustentacular cells, Bowman’s gland cells, and stem cells of the olfactory epithelium. Co-expression analysis of ACE2 and TMPRSS2 and protein-protein interaction among the host and viral proteins elected regulatory cytoskeleton protein-enriched sustentacular cells as the most vulnerable cell-type of the olfactory epithelium. Furthermore, expression, structural and docking analyses of these viral-entry moieties revealed the potential risk of olfactory dysfunction in four additional mammalian species, revealing an evolutionarily conserved susceptibility. In summary, our findings suggest the molecular and cellular rationale of loss of smell in 2019-nCoV infected patients.
krishan57gupta/ROSeq
ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. Takes in the complete filtered and normalized read count matrix, the location of the two sub-populations and the number of cores to be used.
krishan57gupta/iCTC
The goal of iCTC is to detect whether peripheral blood cells have CTCs (circulating tumor cell) or not.
krishan57gupta/BPSC
Beta-Poisson model for single-cell RNA-seq data analyses
krishan57gupta/DOSeq
DOSeq - Modeling expression drop-out for analysis of scRNA-Seq data. DOSeq takes read count matrix and factor for drop-out ratio as input and return the read count matrix with dropout. Here input parameter factor indicates drop-out ratio in expression matrix.
krishan57gupta/HDS
krishan57gupta/my_web
krishan57gupta/ORsurv
survival of patients using ors on TCGA data
krishan57gupta/scanpy
Single-Cell Analysis in Python. Scales to >1M cells.
krishan57gupta/Stardust_package
cell-gene coembedding and analysis pipeline for single cell transcriptomics data
krishan57gupta/stripeDiff
krishan57gupta/UPAHAR
Ultrasound Placental image texture Analysis for prediction of Hypertension during pregnancy using Artificial intelligence Research