Closed kiddo18 closed 1 year ago
Hi, thanks for your interest in FindIT2.
I am wondering whether you can give me a example data that can trigger error info. If you can not upload too much data in github, you can send me email: shangguandong@cemps.ac.cn or shangguandong1996@163.com
By the way, can you post your sessionInfo using sessionInfo()
function ?
Hi, I have received your data. I think it is because your GRange have duplicated names like this
So when I run as.data.frame
, it will report error.
I believe if your add one line code, it will run well
library(FindIT2)
library(TxDb.Hsapiens.BioMart.igis)
GR <- readRDS("GRanges_FindIT2_processed.rds")
# you can choose your own parameter if your species is Hm
# For example, upstream=100000 and downstream=100000
mmAnno_hm <- mm_geneScan(peak_GR = GR, Txdb = TxDb.Hsapiens.BioMart.igis)
# add this code will make the code run well
names(mmAnno_hm) <- NULL
fullRP_hit <- calcRP_TFHit(mmAnno = mmAnno_hm,
Txdb = TxDb.Hsapiens.BioMart.igis,
decay_dist = 10000, report_fullInfo = T)
By the way, I do not know how you produce your GRanges. I recommend you use the loadPeakFile
in FindIT2, which actually use the rtracklayer::import
to read peak file. For example,
peak_path <- system.file("extdata", "ChIP.bed.gz", package = "FindIT2")
# there is no names for my GRanges, so it will not report error.
> loadPeakFile(peak_path)
GRanges object with 4288 ranges and 2 metadata columns:
seqnames ranges strand | feature_id score
<Rle> <IRanges> <Rle> | <character> <numeric>
[1] Chr5 6236-6508 * | peak_14125 27
[2] Chr5 7627-8237 * | peak_14126 51
[3] Chr5 9730-10211 * | peak_14127 32
[4] Chr5 12693-12867 * | peak_14128 22
[5] Chr5 13168-14770 * | peak_14129 519
... ... ... ... . ... ...
[4284] Chr5 26937822-26938526 * | peak_18408 445
[4285] Chr5 26939152-26939267 * | peak_18409 21
[4286] Chr5 26949581-26950335 * | peak_18410 263
[4287] Chr5 26952230-26952558 * | peak_18411 30
[4288] Chr5 26968877-26969091 * | peak_18412 26
-------
seqinfo: 1 sequence from an unspecified genome; no seqlengths
Hi Guan Dong,
I got it to work following your suggestion but not sure what to make of this RP plot
The GRange object is generated from DiffBind from comparing inhibitor of TF vs. control.
Should I be using a different peak file (called by MACS2) as input to the loadPeakFile function? I have the narrowpeak file of each replicate (2 replicates) for each of the drug-treated sample and the control sample.
From the tutorial, it wasn’t clear to me which peak file/Grange object to use to find influential target of my TF by combining with RNA-seq differential gex data
Thank you so much! I opened an issue on the github repository sorry if it’s redundant. Just hoping other people can see your answer too
Hi @shangguandong1996,
I already ran the mmAnno_geneScan function with my
GRanges
object but it says presumably that it couldn't convert todata.frame
from myGRanges
object. Do you know how I can fix this error?fullRP_hit <- calcRP_TFHit(mmAnno = mmAnno_geneScan, Txdb = Txdb, decay_dist = 1000, report_fullInfo = T) calculating peakCenter to TSS using peak-gene pair... 2022-11-26 19:17:18
Error in data.frame(seqnames = as.factor(seqnames(x)), start = start(x), : duplicate row.names: 9462, 9463, 30400, 30401, 30402, 30403, 30404, 30405, 30406, 30407, 30408, 30409, 30410, 30411, 30412, 30413, 30414, 30415, 30416, 30417, 29117, 29111, 29116, 29107, 29105, 29110, 29109, 29113, 29118, 29108, 29114, 29112, 29115, 29119, 29106, 30420, 30421, 30422, 30423, 14381, 14383, 14385, 14403, 14413, 14411, 14388, 14406, 14405, 14393, 14414, 14401, 14397, 14390, 14400, 14392, 14412, 14399, 14394, 14387, 14386, 14391, 14408, 14409, 14407, 14402, 14389, 14404, 14395, 14398, 14410, 14382, 14384, 14396, 9309, 9315, 9310, 9311, 9316, 9312, 9314, 9313, 9307, 9308, 18968, 18954, 18979, 18951, 18965, 18958, 18969, 18948, 18949, 18981, 18955, 18961, 18953, 18982, 18963, 18976, 18971, 18977, 18975, 18950, 18972, 18980, 18957, 18974, 18973, 18978, 18970, 18964, 18952, 18966, 18967, 18946, 18960, 18962, 18956, 18959, 18947, 28876, 28872, 28871, 28875, 28873, 28870, 28869, 28874, 20152, 20157, 20150, 20156, 20160, 20148, 20153, 20151, 20149, 20159, 20168, 20161, 20