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good morning everyone so welcome to that.episode awfully great brain so today we.are talk about very cool format so again.this is the part 1 of a multi-part video.series on variant call format so I don't.know how many part a is but it's gonna.be roughly around the idea of variant.call format so the first part of course.will be about the basic in variant.calling and the reason of why we need to.do variant calling and why is very call.format their ideal format to use in this.case the second part will be about the.actual data itself and how do you open a.very call format file and understand.what is the meaning of every single.component within the file format so that.may be will be 2 videos and lastly will.be follow up by a several example and.try to understand based on example if.understanding is correct on the previous.slides video and so on and so forth so.finally we will finish up with a little.bit of exercise and knowledge tracking.question to see if you know you can.answer those question if you can.congratulations.and again this is not a very advanced.level variant call format video tutorial.it's a relatively straightforward for.people that never being able to.comprehend this format to begin with or.people I never said this before and this.is the first video that you watch and I.hope that will help you a little bit and.if you are if you really are an expert.in the very core format please also do.correct me if I'm wrong because I I also.learned all this thing from some other.online sources and might I might.interpret a certain foul incorrectly ok.so all these actually come from the.manual guide for the very core format.version 4.2 so I'll link the original.document down here below is actually.from Sam to github pages on ok so what.is the variant calling for variant call.format actually this is so a very cool.form a is a specific type a format of a.text file that using bioinformatics for.storing genetic sequence variation so.the format has been developed and we've.ever not the lost skills genotyping and.DNA sequences project such as.project hey so this is very useful to.detecting let's say SMP as well as GWAS.so genome-wide associations that.genome-wide Association studies because.they are able to very efficiently.summarize the differences in multiple.sample in a single file format and the.file format are relatively small.compared to let's say bam files tempo.and so and so forth.okay so they're also just a text file.format it's very easy to open with any.application that you want as long as you.can handle it because for very small.foul let's say within 100 kilobyte you.can just open that in a notepad very.easily and think bigger you might need a.little trick tips and tricks to handle.it so one of it might be our studio so.they're able to handle that quite easily.with varying life function okay so the.objective of this series is basically a.few first of all understand basic.invariant calling when does it use why.is it used.what is it for and what are the.application of the variant calling so.there's a benefit of very cold formats.such as the VCF file format how to read.the metadata how to read the VCF data.and understand the basic significance in.difference in genetic mutation from data.as well as you know a real-world.applications of this variant calling.methodology and so on okay so the basic.variant Co I think I've explained it.multiple times it's a process where.which we identify variants from sequence.data so this is actually just come from.a lot of data let's say like the whole.genome sequencing data where you have.three billion different sequences so.when you can tie a sample to a reference.genome what are the actual differences.between the two sequences and you try to.summarize that differences into a file.so they usually run through an alignment.first before you can actually get your.PCF because VCF is a comparison between.a reference and a sample so you have to.have that too in order for you to.summarize them into a VCF um okay so.this is actually the official definition.and I have my own definition it's just a.way to store genetic data between.separate reference in a way that.everyone can understand and everyone.analyzed and the file format is.a lot smaller than than other faults.such as salmon bat those are my big okay.so you might also see something I'm busy.at so VCF is just a compressed version.of this yes so that kind of.interchangeable not really.interchangeable but it's a more it's a.compressed version of it we'll go to it.later down the video okay so what how do.you visualize the idea of this yeah is.that you can see I have include multiple.sequence alignment so in this case these.are proteins data but you can think of.it as a GC just substitute that in it's.the same so you can think of the first.line over here is the reference sequence.and everything else out there is the.sample so if you look at the line over.here you realize that some mutation in.this tree sample over here some mutation.over here there's a mutation over here.is a mutation over just a mutation over.here so instead of storming this whole.alignment and you're not presented every.single time you want to do the analysis.we can just summarize this big sequence.data into a few lines first of all is.the position and what are the changes.between the reference and sample because.that's the only thing that you know so.if there was touring every single.sequence that you have you can just.store a reference sequence and this year.then you kind of know you can kind of.you can have a reconstruct the sample.sequences based on the VCF and reference.genome directly okay so they're actually.a few genetic modification because this.is actually important to clear out now.before we go down into visa so that you.don't get confused of the terminology.that they use okay so there are four.main types over here the classification.is based on the website that I use there.are there many ways of doing.classifications okay so the first three.type is actually a single nucleotide.forming polymorphism where it's only the.changes between a one single nucleotide.so transition and transversion actually.this our website summarize it very well.where transition is the changes of bases.between.the same shape in this case when an a.which is an adenine is.chin is mutate into a guanine so that is.a transition if you're a is actually.mutate into a cytosine where there's a.different structure we call it a strands.version.okay so transition more likely to happen.because the shape is the same that.usually doesn't cause too much of a.changes in the oval or genetic code as.well as the codon structure as well as.all that thing so a lot of silent.mutation are actually transition what.transversion are usually more severe to.the impact are more severe and usually.introduce a mutation based on that okay.and they are also insertion deletion so.these are we are specifically called.single nucleotide insertion and deletion.so we usually call them in doubt which.is the combination between insertion.deletion so when we are talking about in.doubt that's what we are referring to.so besides single nucleotide.polymorphism and single nucleotide.mutation like there might be a coach um.they get changed directly so it is.normal for let's say transpose some.elements to just jump from one part of.the genome to the other part so damn.fine main types over here for this kind.of cool Chun mutation I don't I'm sure.there's a there's a technical term for.that but for that big chunk mutation so.there might be deletion where you might.missing the whole sequence chunk there.might be in version where the whole.sequence came in first and there might.be insertion where that's one new Chan.inserted in the middle of the genome.this is very very common for very.infection where the viral genome.actually got integrated into the host.their body also be copy number variation.where the same genes get copied multiple.times and I think they use a lot.Anderson for plans so that I can.actually get a stronger genetic traits.and so on so this very similar to let's.say duplication where the the code get.duplicated.okay so this is just a few ways that we.are trying to represent a certain thing.and mostly for use for communications.because the impact of all this thing are.not equal tons let's say an insertion.be as simple as a silent mutation if.they insert into a part of the codon.that doesn't code for anything.nothing changes to the host but if you.have an insertion in the reading frame.you might silence the whole gene or it.might change this you might shift the.reading frame and create a whole new.protein that never never been seen.before so the these are just.understanding of the mutation instead of.the impact we'll look at it impact on.the case-by-case basis because every.single mutation can cause completely.different mutate to yeah my complete.change of phenotype of host or not at.all okay so there also some other file.format that actually achieve somewhat.similar structure so one of it is the.GFR format with the Jeannette general.thicker format or sometimes called the.GTF so that gif tree so it is also very.similar in a way that how they want to.represent changes and mutation and so on.however Geoff have usually stalled the.the genetic data in and is a lot bigger.compared to VCF file they both have.their advantage and disadvantages and.there are certain situations where you.use one over the other but today we can.talk about this yeah okay so finally we.go into what what what what is Visia and.when do we use it so now what the most.prominent example here is to have the to.set up fair in itself in this case you.have to tell self are one of the normal.cell line and one of the tumor cell line.and you sequence both of the our genome.and then you see what are the mutation.between them in this case you might not.even need to secure this whole genome.you might need to sequence just partial.genome or even just example of it using.the same microarray and so and so forth.okay so once we are able to put the two.together we align them to references and.look at the mutation between them you.can very easily isolate what is the.tumor cell and what is the normal cell.just based on the number of new patient.alone because in a lot of time tumor.cell has a lot more mutation compared.no my cell which is white all wet and.they're complete when I got the complete.wake up in the genome which is why.they've become a tumor so these are just.are a whole bunch of tools you can use.to generate the VCF file or to analyze.the VCF all and so on so forth okay so.these are just basic example of a VCF.file again is a text file and you can.easily open up in your file editor so on.I'll try to link example of a VCF down.in description below if not actually you.can look at a slide and these are the.example of a hater.so um just to summarize the thing we.have on this video we have talked about.what is the VCF format we're talk about.what is very calling what the type of.mutation they have and what is the.comparison between VCF and Jeff and what.if the one example we can use the VCF.file which is comparison between a.normal healthy cell and a tumor cell and.just by looking the VCF file we'll be.able to differentiate the two different.cell type with multiple tools that I.included so I'm gonna stop here for.today and we'll move on to the next.video to actually understand why it's.the metadata and what is data within the.VCF file format itself.so thank for watching we'll see you in.the next one bye.

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