c********e
发帖数: 598 | 1 I'd like to hear your input.
1)Microarray,but not RNAseq correlate well with QPCR.
2)Gene expression uniquely determined by RNA-seq is more likely
to be false positive. |
S*********s
发帖数: 304 | 2 感觉RNAseq有很多false positive， QPCR confirm不了 |
l****m
发帖数: 751 | 3 听过一个讲座，human和mouse的一般需求建议用microarray；
其他species，没有完美基因组的，或者有特殊需求，比如想看isoform的建议用RNAseq。
特别少量的用QPCR
实际发文章的时候可能RNAseq更favorable更好接受些。
【在 c********e 的大作中提到】
: I'd like to hear your input.
: 1)Microarray,but not RNAseq correlate well with QPCR.
: 2)Gene expression uniquely determined by RNA-seq is more likely
: to be false positive.
|
g*****n
发帖数: 250 | 4 Microarray 和 RNAseq 都属于呼悠类的。半斤八两。但是，从道理上讲，RNAseq更可
靠。用QPCR来确认？QPCR就可靠？要用Northern，大伙都忘了吧？ |
M*****n
发帖数: 16729 | 5 I have just done an RNAseq, the preliminary analysis not good. many false
hits. |
f*******a
发帖数: 671 | 6 如果只是做differential expression的话，是不是microarray 更成熟一些呢？
觉得RNA-seq再数据分析中还是有不少问题的。 |
M*****n
发帖数: 16729 | 7 但是RNAseq 数据在那里，你可以reanalyze
microarray就只有这么些gene, 不能发现新gene
genome 不完整的话，都是有问题的。
【在 f*******a 的大作中提到】
: 如果只是做differential expression的话，是不是microarray 更成熟一些呢？
: 觉得RNA-seq再数据分析中还是有不少问题的。
|
H****N
发帖数: 997 | 8 In my hands, RNA-seq is much more reliable than microarrays. I have done
side by side comparisons. |
c********e
发帖数: 598 | 9
Did you perform analysis by yourself? Which pipeline did you use?
【在 H****N 的大作中提到】
: In my hands, RNA-seq is much more reliable than microarrays. I have done
: side by side comparisons.
|
H****N
发帖数: 997 | |
|
|
y****t
发帖数: 577 | 11 你那个Microarray数据是不是坏了？
【在 H****N 的大作中提到】
: In my hands, RNA-seq is much more reliable than microarrays. I have done
: side by side comparisons.
|
H****N
发帖数: 997 | |
k****l
发帖数: 279 | 13 I tried confirming gene expression data from RNA-seq by qPCR, 9 out of 10
correlated very well (e.g., RNA-seq shows 8 fold up regulation), PCR shows 8
-16 fold
【在 c********e 的大作中提到】
: I'd like to hear your input.
: 1)Microarray,but not RNAseq correlate well with QPCR.
: 2)Gene expression uniquely determined by RNA-seq is more likely
: to be false positive.
|
s******s
发帖数: 13035 | 14 我觉得microarray主要是做法比较统一, 而seq各实验室手法不一样, 还经常不做
repeat.
不过比如遇到alternative splicing这种, microarray作出来的表达量可能错误百出.
【在 f*******a 的大作中提到】
: 如果只是做differential expression的话，是不是microarray 更成熟一些呢？
: 觉得RNA-seq再数据分析中还是有不少问题的。
|
c********e
发帖数: 598 | 15
8
Which pipeline did you use? Tophat,STAR?Deseq or cufflinks,cuffdiff?
【在 k****l 的大作中提到】
: I tried confirming gene expression data from RNA-seq by qPCR, 9 out of 10
: correlated very well (e.g., RNA-seq shows 8 fold up regulation), PCR shows 8
: -16 fold
|
z*********8
发帖数: 1203 | 16 I used tophat and cufflinks for mapping(DNAnexus) and DESeq for analyzing
differentially expressed gene. DEseq is very nice for beginners like me. I
dont know any R language, but I was able to use the example script to apply
in my case and get the results that I wanted. For pathway analysis, I used
IPA and metacore. |
I*****M
发帖数: 622 | 17 mm你居然是做生物的。。看来是富二代，或者LG是？
apply
【在 z*********8 的大作中提到】
: I used tophat and cufflinks for mapping(DNAnexus) and DESeq for analyzing
: differentially expressed gene. DEseq is very nice for beginners like me. I
: dont know any R language, but I was able to use the example script to apply
: in my case and get the results that I wanted. For pathway analysis, I used
: IPA and metacore.
|
