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Keywords cloud | ADAM kmeans VCF commentPosted pdangiLeave Posted Format Clustering Genome — files Project Data Files Spark Genomics UC flock Applying format | ||||||||||||||||||||||||||||||||||||
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SEO Keywords (Single)
Keyword | Occurrence | Density |
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ADAM | 17 | 0.85 % |
kmeans | 8 | 0.40 % |
VCF | 7 | 0.35 % |
commentPosted | 5 | 0.25 % |
pdangiLeave | 5 | 0.25 % |
Posted | 5 | 0.25 % |
Format | 5 | 0.25 % |
Clustering | 5 | 0.25 % |
Genome | 4 | 0.20 % |
— | 4 | 0.20 % |
files | 4 | 0.20 % |
Project | 4 | 0.20 % |
Data | 3 | 0.15 % |
Files | 3 | 0.15 % |
Spark | 3 | 0.15 % |
Genomics | 3 | 0.15 % |
UC | 2 | 0.10 % |
flock | 2 | 0.10 % |
Applying | 2 | 0.10 % |
format | 2 | 0.10 % |
SEO Keywords (Two Word)
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Posted on | 5 | 0.25 % |
in ADAM | 5 | 0.25 % |
pdangiLeave a | 5 | 0.25 % |
a commentPosted | 5 | 0.25 % |
commentPosted in | 5 | 0.25 % |
1000 Genome | 4 | 0.20 % |
Genome Project | 4 | 0.20 % |
from 1000 | 4 | 0.20 % |
2017 pdangiLeave | 3 | 0.15 % |
for a | 2 | 0.10 % |
on May | 2 | 0.10 % |
Digging Deeper | 2 | 0.10 % |
— Digging | 2 | 0.10 % |
Comparing VCF | 2 | 0.10 % |
VCF Format | 2 | 0.10 % |
Format — | 2 | 0.10 % |
ADAMAvro for | 2 | 0.10 % |
Triallelic site | 2 | 0.10 % |
of the | 2 | 0.10 % |
a Triallelic | 2 | 0.10 % |
SEO Keywords (Three Word)
Keyword | Occurrence | Density | Possible Spam |
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commentPosted in ADAM | 5 | 0.25 % | No |
a commentPosted in | 5 | 0.25 % | No |
pdangiLeave a commentPosted | 5 | 0.25 % | No |
1000 Genome Project | 4 | 0.20 % | No |
from 1000 Genome | 4 | 0.20 % | No |
2017 pdangiLeave a | 3 | 0.15 % | No |
representation in ADAMAvro | 2 | 0.10 % | No |
Comparing VCF Format | 2 | 0.10 % | No |
VCF Format to | 2 | 0.10 % | No |
Format to its | 2 | 0.10 % | No |
its equivalent representation | 2 | 0.10 % | No |
equivalent representation in | 2 | 0.10 % | No |
ADAM to process | 2 | 0.10 % | No |
in ADAMAvro for | 2 | 0.10 % | No |
ADAMAvro for a | 2 | 0.10 % | No |
2016 pdangiLeave a | 2 | 0.10 % | No |
a Triallelic site | 2 | 0.10 % | No |
Posted on May | 2 | 0.10 % | No |
— Digging Deeper | 2 | 0.10 % | No |
Format — Digging | 2 | 0.10 % | No |
SEO Keywords (Four Word)
Keyword | Occurrence | Density | Possible Spam |
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pdangiLeave a commentPosted in | 5 | 0.25 % | No |
a commentPosted in ADAM | 5 | 0.25 % | No |
from 1000 Genome Project | 4 | 0.20 % | No |
2017 pdangiLeave a commentPosted | 3 | 0.15 % | No |
ADAMAvro for a Triallelic | 2 | 0.10 % | No |
Format to its equivalent | 2 | 0.10 % | No |
to its equivalent representation | 2 | 0.10 % | No |
equivalent representation in ADAMAvro | 2 | 0.10 % | No |
representation in ADAMAvro for | 2 | 0.10 % | No |
in ADAMAvro for a | 2 | 0.10 % | No |
commentPosted in ADAM ADAM | 2 | 0.10 % | No |
for a Triallelic site | 2 | 0.10 % | No |
in ADAM Clustering KMeans | 2 | 0.10 % | No |
Format — Digging Deeper | 2 | 0.10 % | No |
ADAM Format — Digging | 2 | 0.10 % | No |
Genomics ADAM Format — | 2 | 0.10 % | No |
Clustering KMeans Machine Learning | 2 | 0.10 % | No |
ADAM Clustering KMeans Machine | 2 | 0.10 % | No |
2016 pdangiLeave a commentPosted | 2 | 0.10 % | No |
Files from 1000 Genome | 2 | 0.10 % | No |
Internal links in - mygenomics.cloud
Technology – MyGenomics
Blog – MyGenomics
Contact – MyGenomics
About Priyanka Dangi – MyGenomics
Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib – MyGenomics
Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. – MyGenomics
Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics
Genomics & ADAM Format — Digging Deeper – MyGenomics
Applying ADAM to process VCF Files from 1000 Genome Project – MyGenomics
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Blog – MyGenomics Skip to content MyGenomics Cloud Scale Genomic Analytics Home Technology Blog ContactWell-nighPriyanka Dangi Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib Posted on July 14, 2016February 11, 2017 pdangiLeave a commentPosted in ADAM, Clustering, K-Means, Machine Learning Our evolutionary history is encoded in a typesetting consisting of series of alphabets {A,T,C,G} that we undeniability our genome. This typesetting is 99.9% identical, to the next individual, in terms of the wiring pairs we siphon in our DNA and yet it narrates a variegated and a unique story well-nigh every individual. The remaining 0.1% […] Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. Posted on June 24, 2016January 23, 2017 pdangiLeave a commentPosted in ADAM, Clustering, K-Means, Machine Learning k-means Clustering Today’s blog will focus on k-means its variants, k-means++ and parallelized variant of k-means++, k-means|| (spark.mllib implementation includes k-means||). There is a surfeit of on-line material on Wikipedia and wonk research papers on these topics that do a far largest job probe into the mathematics & theoretical aspects of some of these algos […] Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site Posted on June 10, 2016January 23, 2017 pdangiLeave a commentPosted in ADAM VCF stands for VariantUndeniabilityFormat. VCF files help represent single wiring pair differences, or polymorphisms (SNPs) and other components of variation like insertions and deletions (INDELs), varying a number of gene repeats (copy number variations, or CNVs) and transposable elements. It is important to note that people are 99.9% genetically similar (about one SNP […] Genomics & ADAM Format — Digging Deeper Posted on May 23, 2016December 13, 2016 pdangiLeave a commentPosted in ADAM ADAM: Genomics Formats and Processing Patterns for Cloud Scale Computing is the original reference from UC Berkeley well-nigh ADAM implementation. ADAM files are 25% smaller on disk than compressed BAM files. ADAM is implemented on top of Avro and Parquet. In 2013, Cloudera and Twitter engineers teamed-up to open-source a new columnar storage format for […] Applying ADAM to process VCF Files from 1000 Genome Project Posted on May 16, 2016December 10, 2016 pdangiLeave a commentPosted in ADAM ADAM from UC Berkeley, provides a set of formats, APIs and implementations for cloud-scale computing of BAM/SAM and VCF files. ADAM uses Parquet format that provides the required interoperability (between variegated languages C++/Java and variegated components of Big Data, ex. Apache Spark) and increasingly importantly space and query efficiencies. Files spewed out of the Sequencing […] Search for: Recent Posts Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site Genomics & ADAM Format — Digging Deeper Applying ADAM to process VCF Files from 1000 Genome Project